{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "QUANTAXIS>> start QUANTAXIS\n",
      "QUANTAXIS>> Welcome to QUANTAXIS, the Version is 1.1.0\n",
      "QUANTAXIS>>  \n",
      " ```````````````````````````````````````````````````````````````````````````````````````````````````````````````````````` \n",
      "  ``########`````##````````##``````````##`````````####````````##```##########````````#``````##``````###```##`````######`` \n",
      "  `##``````## ```##````````##`````````####````````##`##```````##```````##```````````###``````##````##`````##```##`````##` \n",
      "  ##````````##```##````````##````````##`##````````##``##``````##```````##``````````####```````#```##``````##```##``````## \n",
      "  ##````````##```##````````##```````##```##```````##```##`````##```````##`````````##`##```````##`##```````##````##``````` \n",
      "  ##````````##```##````````##``````##`````##``````##````##````##```````##````````##``###```````###````````##`````##`````` \n",
      "  ##````````##```##````````##``````##``````##`````##`````##```##```````##```````##````##```````###````````##``````###```` \n",
      "  ##````````##```##````````##`````##````````##````##``````##``##```````##``````##``````##`````##`##```````##````````##``` \n",
      "  ##````````##```##````````##````#############````##```````##`##```````##`````###########`````##``##``````##`````````##`` \n",
      "  ###```````##```##````````##```##```````````##```##```````##`##```````##````##`````````##```##```##``````##```##`````##` \n",
      "  `##``````###````##``````###``##`````````````##``##````````####```````##```##``````````##``###````##`````##````##`````## \n",
      "  ``#########``````########```##``````````````###`##``````````##```````##``##````````````##`##``````##````##`````###``### \n",
      "  ````````#####`````````````````````````````````````````````````````````````````````````````````````````````````````##``  \n",
      "  ``````````````````````````````````````````````````````````````````````````````````````````````````````````````````````` \n",
      "  ``````````````````````````Copyright``yutiansut``2018``````QUANTITATIVE FINANCIAL FRAMEWORK````````````````````````````` \n",
      "  ``````````````````````````````````````````````````````````````````````````````````````````````````````````````````````` \n",
      " ```````````````````````````````````````````````````````````````````````````````````````````````````````````````````````` \n",
      " ```````````````````````````````````````````````````````````````````````````````````````````````````````````````````````` \n",
      " \n"
     ]
    }
   ],
   "source": [
    "import QUANTAXIS as QA\n",
    "try:\n",
    "    assert QA.__version__>='1.1.0'\n",
    "except AssertionError:\n",
    "    print('pip install QUANTAXIS >= 1.1.0 请升级QUANTAXIS后再运行此示例')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "首先确定你已经完成了对于QUANTAXIS的基础认知,以及在本地存储完毕了QUANTAXIS的数据库\n"
     ]
    }
   ],
   "source": [
    "print('首先确定你已经完成了对于QUANTAXIS的基础认知,以及在本地存储完毕了QUANTAXIS的数据库')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# QUANTAXIS 回测的一些基础知识"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##  QA回测的核心是两个类\n",
    "\n",
    "```\n",
    "QA_BacktestBroker\n",
    "QA_Account\n",
    "```\n",
    "\n",
    "##  回测数据的引入/迭代\n",
    "\n",
    "```\n",
    "QA.QA_fetch_stock_day_adv\n",
    "QA.QA_fetch_stock_min_adv\n",
    "```\n",
    "\n",
    "##  指标的计算\n",
    "\n",
    "```\n",
    "DataStruct.add_func\n",
    "```\n",
    "\n",
    "##  对于账户的灵活运用\n",
    "\n",
    "```\n",
    "QA_Account\n",
    "QA_Risk\n",
    "QA_Portfolio\n",
    "QA_PortfolioView\n",
    "QA_User\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## STEP1 初始化账户,初始化回测broker"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "Account=QA.QA_Account()\n",
    "Broker=QA.QA_BacktestBroker()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "import warnings"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'account_cookie': 'Acc_pgcuAewR',\n",
      " 'allow_sellopen': False,\n",
      " 'allow_t0': False,\n",
      " 'broker': 'backtest',\n",
      " 'cash': [1000000],\n",
      " 'commission_coeff': 0.00025,\n",
      " 'current_time': 'None',\n",
      " 'history': [],\n",
      " 'init_assets': {'cash': 1000000, 'hold': {}},\n",
      " 'margin_level': False,\n",
      " 'market_type': 'stock_cn',\n",
      " 'portfolio_cookie': None,\n",
      " 'quantaxis_version': '1.1.0',\n",
      " 'running_environment': 'backtest',\n",
      " 'running_time': '2018-08-18 00:52:07.746339',\n",
      " 'source': 'account',\n",
      " 'strategy_name': None,\n",
      " 'tax_coeff': 0.0015,\n",
      " 'trade_index': [],\n",
      " 'user_cookie': None}\n"
     ]
    }
   ],
   "source": [
    "# 打印账户的信息\n",
    "try:\n",
    "    from pprint import  pprint as print\n",
    "except:\n",
    "    pass\n",
    "print(Account.message)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 首先讲解Account类:\n",
    "\n",
    "QA_Account在初始化的时候,可以自己指定很多信息:\n",
    "\n",
    "```\n",
    "\n",
    "    QA_Account(\n",
    "        strategy_name=None, user_cookie=None, portfolio_cookie=None, account_cookie=None,\n",
    "        market_type=MARKET_TYPE.STOCK_CN, frequence=FREQUENCE.DAY, broker=BROKER_TYPE.BACKETEST,\n",
    "        init_hold={}, init_cash=1000000, commission_coeff=0.00025, tax_coeff=0.0015,\n",
    "        margin_level=False, allow_t0=False, allow_sellopen=False,\n",
    "        running_environment=RUNNING_ENVIRONMENT.BACKETEST)\n",
    "\n",
    "        :param [str] strategy_name:  策略名称\n",
    "        :param [str] user_cookie:   用户cookie\n",
    "        :param [str] portfolio_cookie: 组合cookie\n",
    "        :param [str] account_cookie:   账户cookie\n",
    "\n",
    "        :param [dict] init_hold         初始化时的股票资产\n",
    "        :param [float] init_cash:         初始化资金\n",
    "        :param [float] commission_coeff:  交易佣金 :默认 万2.5   float 类型\n",
    "        :param [float] tax_coeff:         印花税   :默认 千1.5   float 类型\n",
    "\n",
    "        :param [Bool] margin_level:      保证金比例 默认False\n",
    "        :param [Bool] allow_t0:          是否允许t+0交易  默认False\n",
    "        :param [Bool] allow_sellopen:    是否允许卖空开仓  默认False\n",
    "\n",
    "        :param [QA.PARAM] market_type:   市场类别 默认QA.MARKET_TYPE.STOCK_CN A股股票\n",
    "        :param [QA.PARAM] frequence:     账户级别 默认日线QA.FREQUENCE.DAY\n",
    "        :param [QA.PARAM] broker:        BROEKR类 默认回测 QA.BROKER_TYPE.BACKTEST\n",
    "        :param [QA.PARAM] running_environment 当前运行环境 默认Backtest\n",
    "\n",
    "        # 2018/06/11 init_assets 从float变为dict,并且不作为输入,作为只读属性\n",
    "        #  :param [float] init_assets:       初始资产  默认 1000000 元 （100万）\n",
    "        init_assets:{\n",
    "            cash: xxx,\n",
    "            stock: {'000001':2000},\n",
    "            init_date: '2018-02-05',\n",
    "            init_datetime: '2018-02-05 15:00:00'\n",
    "        }\n",
    "        # 2018/06/11 取消在初始化的时候的cash和history输入\n",
    "        # :param [list] cash:              可用现金  默认 是 初始资产  list 类型\n",
    "        # :param [list] history:           交易历史\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 重设账户初始资金\n",
    "\n",
    "Account.reset_assets(200000)\n",
    "Account.account_cookie='JCSC_EXAMPLE'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'cash': 200000, 'hold': {}}"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Account.init_assets"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Account 有很多方法,暂时不详细展开,我们先直接进入下一步"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# SETP2:引入回测的市场数据"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "引入方法非常简单,直接使用QA_fetch_stock_day_adv系列即可\n",
    "\n",
    "- code 可以是多种多样的选取方式\n",
    "\n",
    "```python\n",
    "1. QA.QA_fetch_stock_list_adv().code.tolist() # 获取全市场的股票代码\n",
    "2. QA.QA_fetch_stock_block_adv().get_block('云计算').code  # 按版块选取\n",
    "3. code= ['000001','000002'] # 自己指定\n",
    "```\n",
    "- 数据获取后,to_qfq() 即可获得前复权数据\n",
    "\n",
    "```python\n",
    "data=DataSturct.to_qfq()\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "# QA.QA_fetch_stock_list_adv().code.tolist()\n",
    "# QA.QA_fetch_stock_block_adv().get_block('云计算').code\n",
    "codelist=QA.QA_fetch_stock_block_adv().get_block('云计算').code"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "data=QA.QA_fetch_stock_day_adv(codelist,'2017-09-01','2018-05-20')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "< QA_DataStruct_Stock_day with 109 securities >"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "data=data.to_qfq()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "# data.data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## STEP3:计算一些指标"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "指标的计算可以在回测前,也可以在回测中进行\n",
    "\n",
    "回测前的计算则是批量计算,效率较高\n",
    "\n",
    "回测中的计算,效率略低,但代码量较小,易于理解\n",
    "\n",
    "PS: 指标的相关介绍参见 [QUANTAXIS的指标系统](https://github.com/QUANTAXIS/QUANTAXIS/blob/master/Documents/indicators.md)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "def MACD_JCSC(dataframe,SHORT=12,LONG=26,M=9):\n",
    "    \"\"\"\n",
    "    1.DIF向上突破DEA，买入信号参考。\n",
    "    2.DIF向下跌破DEA，卖出信号参考。\n",
    "    \"\"\"\n",
    "    CLOSE=dataframe.close\n",
    "    DIFF =QA.EMA(CLOSE,SHORT) - QA.EMA(CLOSE,LONG)\n",
    "    DEA = QA.EMA(DIFF,M)\n",
    "    MACD =2*(DIFF-DEA)\n",
    "\n",
    "    CROSS_JC=QA.CROSS(DIFF,DEA)\n",
    "    CROSS_SC=QA.CROSS(DEA,DIFF)\n",
    "    ZERO=0\n",
    "    return pd.DataFrame({'DIFF':DIFF,'DEA':DEA,'MACD':MACD,'CROSS_JC':CROSS_JC,'CROSS_SC':CROSS_SC,'ZERO':ZERO})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "ind=data.add_func(MACD_JCSC)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1eb505be128>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ind.xs(codelist[0],level=1)['2018-01'].plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>DIFF</th>\n",
       "      <th>DEA</th>\n",
       "      <th>MACD</th>\n",
       "      <th>CROSS_JC</th>\n",
       "      <th>CROSS_SC</th>\n",
       "      <th>ZERO</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2018-01-02</th>\n",
       "      <td>0.062832</td>\n",
       "      <td>0.034908</td>\n",
       "      <td>0.055848</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-03</th>\n",
       "      <td>0.083081</td>\n",
       "      <td>0.044543</td>\n",
       "      <td>0.077076</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-04</th>\n",
       "      <td>0.096405</td>\n",
       "      <td>0.054915</td>\n",
       "      <td>0.082979</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-05</th>\n",
       "      <td>0.101761</td>\n",
       "      <td>0.064284</td>\n",
       "      <td>0.074953</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-08</th>\n",
       "      <td>0.096831</td>\n",
       "      <td>0.070794</td>\n",
       "      <td>0.052074</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-09</th>\n",
       "      <td>0.087880</td>\n",
       "      <td>0.074211</td>\n",
       "      <td>0.027338</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-10</th>\n",
       "      <td>0.127678</td>\n",
       "      <td>0.084904</td>\n",
       "      <td>0.085548</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-11</th>\n",
       "      <td>0.239488</td>\n",
       "      <td>0.115821</td>\n",
       "      <td>0.247333</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-12</th>\n",
       "      <td>0.315590</td>\n",
       "      <td>0.155775</td>\n",
       "      <td>0.319631</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-15</th>\n",
       "      <td>0.413861</td>\n",
       "      <td>0.207392</td>\n",
       "      <td>0.412937</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-16</th>\n",
       "      <td>0.435121</td>\n",
       "      <td>0.252938</td>\n",
       "      <td>0.364367</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-17</th>\n",
       "      <td>0.358336</td>\n",
       "      <td>0.274018</td>\n",
       "      <td>0.168637</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-18</th>\n",
       "      <td>0.281338</td>\n",
       "      <td>0.275482</td>\n",
       "      <td>0.011713</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-19</th>\n",
       "      <td>0.220198</td>\n",
       "      <td>0.264425</td>\n",
       "      <td>-0.088454</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-22</th>\n",
       "      <td>0.158625</td>\n",
       "      <td>0.243265</td>\n",
       "      <td>-0.169280</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-23</th>\n",
       "      <td>0.099806</td>\n",
       "      <td>0.214573</td>\n",
       "      <td>-0.229534</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-24</th>\n",
       "      <td>0.070925</td>\n",
       "      <td>0.185844</td>\n",
       "      <td>-0.229837</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-25</th>\n",
       "      <td>0.041907</td>\n",
       "      <td>0.157056</td>\n",
       "      <td>-0.230298</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-26</th>\n",
       "      <td>0.027466</td>\n",
       "      <td>0.131138</td>\n",
       "      <td>-0.207344</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-29</th>\n",
       "      <td>-0.001704</td>\n",
       "      <td>0.104570</td>\n",
       "      <td>-0.212547</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-30</th>\n",
       "      <td>-0.053246</td>\n",
       "      <td>0.073007</td>\n",
       "      <td>-0.252505</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-31</th>\n",
       "      <td>-0.121729</td>\n",
       "      <td>0.034059</td>\n",
       "      <td>-0.311578</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                DIFF       DEA      MACD  CROSS_JC  CROSS_SC  ZERO\n",
       "date                                                              \n",
       "2018-01-02  0.062832  0.034908  0.055848         0         0     0\n",
       "2018-01-03  0.083081  0.044543  0.077076         0         0     0\n",
       "2018-01-04  0.096405  0.054915  0.082979         0         0     0\n",
       "2018-01-05  0.101761  0.064284  0.074953         0         0     0\n",
       "2018-01-08  0.096831  0.070794  0.052074         0         0     0\n",
       "2018-01-09  0.087880  0.074211  0.027338         0         0     0\n",
       "2018-01-10  0.127678  0.084904  0.085548         0         0     0\n",
       "2018-01-11  0.239488  0.115821  0.247333         0         0     0\n",
       "2018-01-12  0.315590  0.155775  0.319631         0         0     0\n",
       "2018-01-15  0.413861  0.207392  0.412937         0         0     0\n",
       "2018-01-16  0.435121  0.252938  0.364367         0         0     0\n",
       "2018-01-17  0.358336  0.274018  0.168637         0         0     0\n",
       "2018-01-18  0.281338  0.275482  0.011713         0         0     0\n",
       "2018-01-19  0.220198  0.264425 -0.088454         0         1     0\n",
       "2018-01-22  0.158625  0.243265 -0.169280         0         0     0\n",
       "2018-01-23  0.099806  0.214573 -0.229534         0         0     0\n",
       "2018-01-24  0.070925  0.185844 -0.229837         0         0     0\n",
       "2018-01-25  0.041907  0.157056 -0.230298         0         0     0\n",
       "2018-01-26  0.027466  0.131138 -0.207344         0         0     0\n",
       "2018-01-29 -0.001704  0.104570 -0.212547         0         0     0\n",
       "2018-01-30 -0.053246  0.073007 -0.252505         0         0     0\n",
       "2018-01-31 -0.121729  0.034059 -0.311578         0         0     0"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ind.xs(codelist[0],level=1)['2018-01']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th rowspan=\"30\" valign=\"top\">2018-01-02</th>\n",
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       "      <th>002456</th>\n",
       "      <td>-0.644033</td>\n",
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       "      <th>...</th>\n",
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       "    <tr>\n",
       "      <th rowspan=\"30\" valign=\"top\">2018-01-31</th>\n",
       "      <th>600225</th>\n",
       "      <td>-0.058853</td>\n",
       "      <td>-0.031449</td>\n",
       "      <td>-0.054807</td>\n",
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       "      <th>600289</th>\n",
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       "      <th>600385</th>\n",
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       "      <td>-0.069449</td>\n",
       "      <td>-0.013864</td>\n",
       "      <td>-0.111170</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>600601</th>\n",
       "      <td>-0.071518</td>\n",
       "      <td>-0.047553</td>\n",
       "      <td>-0.047930</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>600602</th>\n",
       "      <td>-0.020619</td>\n",
       "      <td>0.022803</td>\n",
       "      <td>-0.086844</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>600633</th>\n",
       "      <td>0.138275</td>\n",
       "      <td>0.143204</td>\n",
       "      <td>-0.009859</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>600718</th>\n",
       "      <td>-0.372869</td>\n",
       "      <td>-0.327002</td>\n",
       "      <td>-0.091732</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>600728</th>\n",
       "      <td>-0.229074</td>\n",
       "      <td>-0.185714</td>\n",
       "      <td>-0.086721</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>600756</th>\n",
       "      <td>-0.269601</td>\n",
       "      <td>-0.191433</td>\n",
       "      <td>-0.156336</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>600767</th>\n",
       "      <td>-0.135812</td>\n",
       "      <td>-0.156087</td>\n",
       "      <td>0.040549</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>600770</th>\n",
       "      <td>-0.135974</td>\n",
       "      <td>-0.112889</td>\n",
       "      <td>-0.046169</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>600797</th>\n",
       "      <td>-0.134989</td>\n",
       "      <td>-0.070951</td>\n",
       "      <td>-0.128076</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>600804</th>\n",
       "      <td>-0.353543</td>\n",
       "      <td>-0.371659</td>\n",
       "      <td>0.036233</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>600845</th>\n",
       "      <td>0.292773</td>\n",
       "      <td>0.365709</td>\n",
       "      <td>-0.145873</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>600850</th>\n",
       "      <td>-0.756647</td>\n",
       "      <td>-0.658652</td>\n",
       "      <td>-0.195991</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>600996</th>\n",
       "      <td>0.036689</td>\n",
       "      <td>0.032597</td>\n",
       "      <td>0.008183</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>601360</th>\n",
       "      <td>0.738888</td>\n",
       "      <td>0.826734</td>\n",
       "      <td>-0.175693</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>601928</th>\n",
       "      <td>0.004650</td>\n",
       "      <td>-0.007193</td>\n",
       "      <td>0.023685</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>603003</th>\n",
       "      <td>-0.097565</td>\n",
       "      <td>-0.065917</td>\n",
       "      <td>-0.063296</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>603019</th>\n",
       "      <td>-0.584812</td>\n",
       "      <td>-0.860198</td>\n",
       "      <td>0.550773</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>603138</th>\n",
       "      <td>-1.169107</td>\n",
       "      <td>-0.253536</td>\n",
       "      <td>-1.831142</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>603528</th>\n",
       "      <td>-0.064889</td>\n",
       "      <td>-0.128929</td>\n",
       "      <td>0.128080</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>603881</th>\n",
       "      <td>-1.189179</td>\n",
       "      <td>-0.934114</td>\n",
       "      <td>-0.510130</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2278 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                       DIFF       DEA      MACD  CROSS_JC  CROSS_SC  ZERO\n",
       "date       code                                                          \n",
       "2018-01-02 000021  0.062832  0.034908  0.055848         0         0     0\n",
       "           000063  0.350531  0.539474 -0.377886         0         0     0\n",
       "           000066 -0.103693 -0.164662  0.121938         0         0     0\n",
       "           000070 -0.298122 -0.297769 -0.000706         0         0     0\n",
       "           000100 -0.111283 -0.109635 -0.003296         0         0     0\n",
       "           000555       NaN       NaN       NaN         0         0     0\n",
       "           000611  0.085137  0.038461  0.093353         0         0     0\n",
       "           000665 -0.128508 -0.179685  0.102356         0         0     0\n",
       "           000836 -0.094147       NaN       NaN         0         0     0\n",
       "           000938  1.251292  0.414957  1.672669         0         0     0\n",
       "           000948 -0.138808 -0.163646  0.049677         0         0     0\n",
       "           000977  0.147007  0.089165  0.115685         0         0     0\n",
       "           002063 -0.000718 -0.041517  0.081599         0         0     0\n",
       "           002065 -0.330897 -0.311772 -0.038251         0         0     0\n",
       "           002093  0.071611  0.040341  0.062539         0         0     0\n",
       "           002095 -0.141841 -0.246130  0.208579         0         0     0\n",
       "           002195 -0.150915 -0.158826  0.015820         1         0     0\n",
       "           002197 -0.039920 -0.026400 -0.027039         0         0     0\n",
       "           002268 -0.282747 -0.095097 -0.375300         0         0     0\n",
       "           002279 -0.207586 -0.179862 -0.055448         0         0     0\n",
       "           002281  0.155791  0.417276 -0.522969         0         0     0\n",
       "           002301 -0.029081  0.022214 -0.102589         0         0     0\n",
       "           002315 -0.741722 -0.618039 -0.247365         0         0     0\n",
       "           002335 -0.672783 -0.623881 -0.097803         0         0     0\n",
       "           002368 -0.415162 -0.345593 -0.139139         0         0     0\n",
       "           002396 -0.372709 -0.313333 -0.118752         0         0     0\n",
       "           002415  0.137828  0.117979  0.039697         0         0     0\n",
       "           002417 -0.315567 -0.213388 -0.204357         0         0     0\n",
       "           002439 -0.110393  0.036686 -0.294157         0         0     0\n",
       "           002456 -0.644033 -0.682755  0.077443         1         0     0\n",
       "...                     ...       ...       ...       ...       ...   ...\n",
       "2018-01-31 600225 -0.058853 -0.031449 -0.054807         0         0     0\n",
       "           600289 -1.171529 -1.205996  0.068934         0         0     0\n",
       "           600385 -0.338182 -0.307123 -0.062117         0         0     0\n",
       "           600410 -0.088613 -0.075791 -0.025643         0         1     0\n",
       "           600522 -0.557657 -0.468933 -0.177448         0         0     0\n",
       "           600536 -0.648704 -0.408761 -0.479886         0         0     0\n",
       "           600588  0.327150  0.199457  0.255386         0         0     0\n",
       "           600589  0.004017  0.018157 -0.028280         0         1     0\n",
       "           600590 -0.192047 -0.194900  0.005705         0         0     0\n",
       "           600595 -0.069449 -0.013864 -0.111170         0         0     0\n",
       "           600601 -0.071518 -0.047553 -0.047930         0         0     0\n",
       "           600602 -0.020619  0.022803 -0.086844         0         0     0\n",
       "           600633  0.138275  0.143204 -0.009859         0         1     0\n",
       "           600718 -0.372869 -0.327002 -0.091732         0         0     0\n",
       "           600728 -0.229074 -0.185714 -0.086721         0         0     0\n",
       "           600756 -0.269601 -0.191433 -0.156336         0         0     0\n",
       "           600767 -0.135812 -0.156087  0.040549         0         0     0\n",
       "           600770 -0.135974 -0.112889 -0.046169         0         0     0\n",
       "           600797 -0.134989 -0.070951 -0.128076         0         0     0\n",
       "           600804 -0.353543 -0.371659  0.036233         0         0     0\n",
       "           600845  0.292773  0.365709 -0.145873         0         0     0\n",
       "           600850 -0.756647 -0.658652 -0.195991         0         0     0\n",
       "           600996  0.036689  0.032597  0.008183         0         0     0\n",
       "           601360  0.738888  0.826734 -0.175693         0         0     0\n",
       "           601928  0.004650 -0.007193  0.023685         0         0     0\n",
       "           603003 -0.097565 -0.065917 -0.063296         0         0     0\n",
       "           603019 -0.584812 -0.860198  0.550773         0         0     0\n",
       "           603138 -1.169107 -0.253536 -1.831142         0         0     0\n",
       "           603528 -0.064889 -0.128929  0.128080         0         0     0\n",
       "           603881 -1.189179 -0.934114 -0.510130         0         0     0\n",
       "\n",
       "[2278 rows x 6 columns]"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ind.loc['2018-01',slice(None)]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# SETP4:选取回测的开始和结束日期,构建回测"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['JCSC_EXAMPLE', '2018-01-02 00:00:00', '2018-01-02 00:00:00', '002195', None, 1, 5.91, 5.91, 'trade_success', 1000, 1000, 5915.0, 0, 'Order_AGZefuXd', 'Trade_UDtyK1Vm']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-01-02 00:00:00', '2018-01-02 00:00:00', '002456', None, 1, 20.78, 20.78, 'trade_success', 1000, 1000, 20785.195, 0, 'Order_qOuEB4fo', 'Trade_DkUcde6T']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-01-02 00:00:00', '2018-01-02 00:00:00', '002544', None, 1, 15.85, 15.85, 'trade_success', 1000, 1000, 15855.0, 0, 'Order_ripYwt6L', 'Trade_JfdrGHs7']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-01-02 00:00:00', '2018-01-02 00:00:00', '300290', None, 1, 8.71, 8.71, 'trade_success', 1000, 1000, 8715.0, 0, 'Order_ph50Tje9', 'Trade_OAMc0nCN']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-01-02 00:00:00', '2018-01-02 00:00:00', '300367', None, 1, 15.39, 15.39, 'trade_success', 1000, 1000, 15395.0, 0, 'Order_YvlByWfD', 'Trade_LbpR6WtI']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-01-02 00:00:00', '2018-01-02 00:00:00', '600105', None, 1, 6.58, 6.58, 'trade_success', 1000, 1000, 6585.0, 0, 'Order_8sBTIvLO', 'Trade_BiOS3Ztq']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-01-02 00:00:00', '2018-01-02 00:00:00', '600797', None, 1, 11.87, 11.87, 'trade_success', 1000, 1000, 11875.0, 0, 'Order_whQIWHBi', 'Trade_SRGx3zgh']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-01-03 00:00:00', '2018-01-03 00:00:00', '000070', None, 1, 9.52, 9.52, 'trade_success', 1000, 1000, 9525.0, 0, 'Order_wDPTJiRh', 'Trade_N5UtmxRI']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-01-03 00:00:00', '2018-01-03 00:00:00', '000100', None, 1, 3.99, 3.99, 'trade_success', 1000, 1000, 3995.0, 0, 'Order_f8yNTPHe', 'Trade_X35rycEk']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-01-03 00:00:00', '2018-01-03 00:00:00', '002065', None, 1, 8.53, 8.53, 'trade_success', 1000, 1000, 8535.0, 0, 'Order_x5k8PvbA', 'Trade_fTvkUK8d']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-01-03 00:00:00', '2018-01-03 00:00:00', '002335', None, 1, 30.04, 30.0405515678, 'trade_success', 1000, 1000, 30048.06170569195, 0, 'Order_jKYkEcmX', 'Trade_eETIS197']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-01-03 00:00:00', '2018-01-03 00:00:00', '300036', None, 1, 15.78, 15.7777305703, 'trade_success', 1000, 1000, 15782.730570299998, 0, 'Order_iB3KzEPv', 'Trade_R7n2a9Bx']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-01-03 00:00:00', '2018-01-03 00:00:00', '600198', None, 1, 11.65, 11.65, 'trade_success', 1000, 1000, 11655.0, 0, 'Order_eFZH05bs', 'Trade_npL4HvAb']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-01-03 00:00:00', '2018-01-03 00:00:00', '600718', None, 1, 15.0, 15.0, 'trade_success', 1000, 1000, 15005.0, 0, 'Order_K3MjyXZo', 'Trade_xvR7tZc9']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-01-03 00:00:00', '2018-01-03 00:00:00', '600804', None, 1, 17.93, 17.93, 'trade_success', 1000, 1000, 17935.0, 0, 'Order_EdD6u1Cb', 'Trade_yk9gJsET']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-01-03 00:00:00', '2018-01-03 00:00:00', '600850', None, 1, 19.95, 19.95, 'trade_success', 1000, 1000, 19955.0, 0, 'Order_jihSr8uH', 'Trade_pgWl246P']\n",
      "receive deal\n",
      "2124.3225000000275\n",
      "NOT ENOUGH MONEY FOR Order_jihSr8uH\n",
      "['JCSC_EXAMPLE', '2018-01-03 00:00:00', '2018-01-03 00:00:00', '603019', None, 1, 42.53, 42.5288071646, 'trade_success', 1000, 1000, 42539.439366391154, 0, 'Order_oYTjzZ0b', 'Trade_1MvQ6i5Y']\n",
      "receive deal\n",
      "2124.3225000000275\n",
      "NOT ENOUGH MONEY FOR Order_oYTjzZ0b\n",
      "['JCSC_EXAMPLE', '2018-01-04 00:00:00', '2018-01-04 00:00:00', '002396', None, 1, 21.98, 21.98, 'trade_success', 1000, 1000, 21985.495, 0, 'Order_wofhJYzk', 'Trade_4MZ1VJ5h']\n",
      "receive deal\n",
      "2124.3225000000275\n",
      "NOT ENOUGH MONEY FOR Order_wofhJYzk\n",
      "['JCSC_EXAMPLE', '2018-01-04 00:00:00', '2018-01-04 00:00:00', '300271', None, 1, 15.72, 15.72, 'trade_success', 1000, 1000, 15725.0, 0, 'Order_ldHzCi7M', 'Trade_9HvfrFPX']\n",
      "receive deal\n",
      "2124.3225000000275\n",
      "NOT ENOUGH MONEY FOR Order_ldHzCi7M\n",
      "['JCSC_EXAMPLE', '2018-01-04 00:00:00', '2018-01-04 00:00:00', '300287', None, 1, 7.47, 7.47, 'trade_success', 1000, 1000, 7475.0, 0, 'Order_ac17oQMG', 'Trade_YIUJDnks']\n",
      "receive deal\n",
      "2124.3225000000275\n",
      "NOT ENOUGH MONEY FOR Order_ac17oQMG\n",
      "['JCSC_EXAMPLE', '2018-01-04 00:00:00', '2018-01-04 00:00:00', '300379', None, 1, 12.86, 12.86, 'trade_success', 1000, 1000, 12865.0, 0, 'Order_q7yWhBSM', 'Trade_8NzCVtvB']\n",
      "receive deal\n",
      "2124.3225000000275\n",
      "NOT ENOUGH MONEY FOR Order_q7yWhBSM\n",
      "['JCSC_EXAMPLE', '2018-01-04 00:00:00', '2018-01-04 00:00:00', '601360', None, 1, 61.19, 61.19, 'trade_success', 1000, 1000, 61205.2975, 0, 'Order_afnKsDLE', 'Trade_d3Kb9YBv']\n",
      "receive deal\n",
      "2124.3225000000275\n",
      "NOT ENOUGH MONEY FOR Order_afnKsDLE\n",
      "['JCSC_EXAMPLE', '2018-01-05 00:00:00', '2018-01-05 00:00:00', '002279', None, 1, 10.6, 10.6, 'trade_success', 1000, 1000, 10605.0, 0, 'Order_3eHFCuiS', 'Trade_S3QarRiq']\n",
      "receive deal\n",
      "2124.3225000000275\n",
      "NOT ENOUGH MONEY FOR Order_3eHFCuiS\n",
      "['JCSC_EXAMPLE', '2018-01-05 00:00:00', '2018-01-05 00:00:00', '300051', None, 1, 9.8, 9.8, 'trade_success', 1000, 1000, 9805.0, 0, 'Order_c035OI6W', 'Trade_imDa5QxL']\n",
      "receive deal\n",
      "2124.3225000000275\n",
      "NOT ENOUGH MONEY FOR Order_c035OI6W\n",
      "['JCSC_EXAMPLE', '2018-01-08 00:00:00', '2018-01-08 00:00:00', '300020', None, 1, 11.98, 11.98, 'trade_success', 1000, 1000, 11985.0, 0, 'Order_fHJv5FsI', 'Trade_Kj5PHhxS']\n",
      "receive deal\n",
      "2124.3225000000275\n",
      "NOT ENOUGH MONEY FOR Order_fHJv5FsI\n",
      "['JCSC_EXAMPLE', '2018-01-08 00:00:00', '2018-01-08 00:00:00', '600601', None, 1, 3.68, 3.68, 'trade_success', 1000, 1000, 3685.0, 0, 'Order_RP6e4Q2H', 'Trade_LMntTXuz']\n",
      "receive deal\n",
      "2124.3225000000275\n",
      "NOT ENOUGH MONEY FOR Order_RP6e4Q2H\n",
      "['JCSC_EXAMPLE', '2018-01-09 00:00:00', '2018-01-09 00:00:00', '002315', None, 1, 21.92, 21.92, 'trade_success', 1000, 1000, 21925.48, 0, 'Order_9ZBqL0vX', 'Trade_3o1bzNnD']\n",
      "receive deal\n",
      "2124.3225000000275\n",
      "NOT ENOUGH MONEY FOR Order_9ZBqL0vX\n",
      "['JCSC_EXAMPLE', '2018-01-09 00:00:00', '2018-01-09 00:00:00', '300044', None, 1, 8.51, 8.5108416798, 'trade_success', 1000, 1000, 8515.8416798, 0, 'Order_M5F3kuqg', 'Trade_EnBDeWyr']\n",
      "receive deal\n",
      "2124.3225000000275\n",
      "NOT ENOUGH MONEY FOR Order_M5F3kuqg\n",
      "['JCSC_EXAMPLE', '2018-01-09 00:00:00', '2018-01-09 00:00:00', '300367', None, -1, 14.91, 14.905000000000001, 'trade_success', 1000, 1000, 14932.357500000002, 0, 'Order_KYdA3NQ9', 'Trade_fiZVxdwg']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-01-10 00:00:00', '2018-01-10 00:00:00', '002268', None, 1, 24.01, 24.01, 'trade_success', 1000, 1000, 24016.0025, 0, 'Order_bS8AuZpC', 'Trade_0nCZPh57']\n",
      "receive deal\n",
      "17060.41500000003\n",
      "NOT ENOUGH MONEY FOR Order_bS8AuZpC\n",
      "['JCSC_EXAMPLE', '2018-01-10 00:00:00', '2018-01-10 00:00:00', '300245', None, 1, 13.8, 13.8, 'trade_success', 1000, 1000, 13805.0, 0, 'Order_uCE5pWke', 'Trade_zAOpRNe3']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-01-10 00:00:00', '2018-01-10 00:00:00', '300365', None, 1, 16.08, 16.0754385965, 'trade_success', 1000, 1000, 16080.4385965, 0, 'Order_WS1IinTQ', 'Trade_y9W5rxwQ']\n",
      "receive deal\n",
      "3236.2650000000303\n",
      "NOT ENOUGH MONEY FOR Order_WS1IinTQ\n",
      "['JCSC_EXAMPLE', '2018-01-10 00:00:00', '2018-01-10 00:00:00', '300608', None, 1, 30.43, 30.43, 'trade_success', 1000, 1000, 30437.6075, 0, 'Order_XBoxEQWS', 'Trade_iRBQh1UI']\n",
      "receive deal\n",
      "3236.2650000000303\n",
      "NOT ENOUGH MONEY FOR Order_XBoxEQWS\n",
      "['JCSC_EXAMPLE', '2018-01-11 00:00:00', '2018-01-11 00:00:00', '002197', None, 1, 12.82, 12.82, 'trade_success', 1000, 1000, 12825.0, 0, 'Order_Zys8CE9t', 'Trade_kq36Nhez']\n",
      "receive deal\n",
      "3236.2650000000303\n",
      "NOT ENOUGH MONEY FOR Order_Zys8CE9t\n",
      "['JCSC_EXAMPLE', '2018-01-11 00:00:00', '2018-01-11 00:00:00', '002281', None, 1, 31.79, 31.79, 'trade_success', 1000, 1000, 31797.9475, 0, 'Order_oW80LZ6X', 'Trade_mPGEJsRh']\n",
      "receive deal\n",
      "3236.2650000000303\n",
      "NOT ENOUGH MONEY FOR Order_oW80LZ6X\n",
      "['JCSC_EXAMPLE', '2018-01-11 00:00:00', '2018-01-11 00:00:00', '300025', None, 1, 6.2, 6.2, 'trade_success', 1000, 1000, 6205.0, 0, 'Order_4l9AcwfC', 'Trade_gtfGl73p']\n",
      "receive deal\n",
      "3236.2650000000303\n",
      "NOT ENOUGH MONEY FOR Order_4l9AcwfC\n",
      "['JCSC_EXAMPLE', '2018-01-11 00:00:00', '2018-01-11 00:00:00', '300229', None, 1, 15.19, 15.19, 'trade_success', 1000, 1000, 15195.0, 0, 'Order_5DjnVJAu', 'Trade_6ugSxnjZ']\n",
      "receive deal\n",
      "3236.2650000000303\n",
      "NOT ENOUGH MONEY FOR Order_5DjnVJAu\n",
      "['JCSC_EXAMPLE', '2018-01-11 00:00:00', '2018-01-11 00:00:00', '300271', None, 1, 15.78, 15.78, 'trade_success', 1000, 1000, 15785.0, 0, 'Order_yOJgskUz', 'Trade_ZBwWnMVP']\n",
      "receive deal\n",
      "3236.2650000000303\n",
      "NOT ENOUGH MONEY FOR Order_yOJgskUz\n",
      "['JCSC_EXAMPLE', '2018-01-11 00:00:00', '2018-01-11 00:00:00', '300311', None, 1, 14.09, 14.09, 'trade_success', 1000, 1000, 14095.0, 0, 'Order_AZgqdmjz', 'Trade_jpMuEZWQ']\n",
      "receive deal\n",
      "3236.2650000000303\n",
      "NOT ENOUGH MONEY FOR Order_AZgqdmjz\n",
      "['JCSC_EXAMPLE', '2018-01-11 00:00:00', '2018-01-11 00:00:00', '300367', None, 1, 15.04, 15.04, 'trade_success', 1000, 1000, 15045.0, 0, 'Order_YkZeaEiF', 'Trade_CVxklmfK']\n",
      "receive deal\n",
      "3236.2650000000303\n",
      "NOT ENOUGH MONEY FOR Order_YkZeaEiF\n",
      "['JCSC_EXAMPLE', '2018-01-11 00:00:00', '2018-01-11 00:00:00', '600588', None, 1, 17.01, 17.01492019, 'trade_success', 1000, 1000, 17019.92019, 0, 'Order_5igmfrn7', 'Trade_heXYC2An']\n",
      "receive deal\n",
      "3236.2650000000303\n",
      "NOT ENOUGH MONEY FOR Order_5igmfrn7\n",
      "['JCSC_EXAMPLE', '2018-01-11 00:00:00', '2018-01-11 00:00:00', '600601', None, 1, 3.69, 3.69, 'trade_success', 1000, 1000, 3695.0, 0, 'Order_nAc52Jea', 'Trade_lvuNmS58']\n",
      "receive deal\n",
      "3236.2650000000303\n",
      "NOT ENOUGH MONEY FOR Order_nAc52Jea\n",
      "['JCSC_EXAMPLE', '2018-01-11 00:00:00', '2018-01-11 00:00:00', '600850', None, 1, 19.55, 19.55, 'trade_success', 1000, 1000, 19555.0, 0, 'Order_Xzq8s3k7', 'Trade_OGtpnBVu']\n",
      "receive deal\n",
      "3236.2650000000303\n",
      "NOT ENOUGH MONEY FOR Order_Xzq8s3k7\n",
      "['JCSC_EXAMPLE', '2018-01-11 00:00:00', '2018-01-11 00:00:00', '603138', None, 1, 51.75, 51.75, 'trade_success', 1000, 1000, 51762.9375, 0, 'Order_aoU8hveP', 'Trade_jnmFe7q2']\n",
      "receive deal\n",
      "3236.2650000000303\n",
      "NOT ENOUGH MONEY FOR Order_aoU8hveP\n",
      "['JCSC_EXAMPLE', '2018-01-12 00:00:00', '2018-01-12 00:00:00', '002095', None, 1, 34.75, 34.75, 'trade_success', 1000, 1000, 34758.6875, 0, 'Order_AGDz9VSs', 'Trade_C7JOow2Q']\n",
      "receive deal\n",
      "3236.2650000000303\n",
      "NOT ENOUGH MONEY FOR Order_AGDz9VSs\n",
      "['JCSC_EXAMPLE', '2018-01-12 00:00:00', '2018-01-12 00:00:00', '002456', None, -1, 19.84, 19.84, 'trade_success', 1000.0, 1000.0, 19874.76, 0, 'Order_p5J1Paxo', 'Trade_XkQdvGgh']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-01-12 00:00:00', '2018-01-12 00:00:00', '300052', None, 1, 15.85, 15.85, 'trade_success', 1000, 1000, 15855.0, 0, 'Order_GOfSMKya', 'Trade_N9YeECnd']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-01-12 00:00:00', '2018-01-12 00:00:00', '300113', None, 1, 18.92, 18.92, 'trade_success', 1000, 1000, 18925.0, 0, 'Order_1ZtY6JLh', 'Trade_b1vIi2H5']\n",
      "receive deal\n",
      "7233.24750000003\n",
      "NOT ENOUGH MONEY FOR Order_1ZtY6JLh\n",
      "['JCSC_EXAMPLE', '2018-01-12 00:00:00', '2018-01-12 00:00:00', '300128', None, 1, 10.55, 10.55, 'trade_success', 1000, 1000, 10555.0, 0, 'Order_8sSNOEPD', 'Trade_PgJsEfo9']\n",
      "receive deal\n",
      "7233.24750000003\n",
      "NOT ENOUGH MONEY FOR Order_8sSNOEPD\n",
      "['JCSC_EXAMPLE', '2018-01-15 00:00:00', '2018-01-15 00:00:00', '300036', None, -1, 14.49, 14.48863523355, 'trade_success', 1000.0, 1000.0, 14515.368186400325, 0, 'Order_kK1V8DEQ', 'Trade_uSDtYAiP']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-01-15 00:00:00', '2018-01-15 00:00:00', '300245', None, -1, 13.38, 13.375, 'trade_success', 1000.0, 1000.0, 13400.0625, 0, 'Order_qcGuE2ij', 'Trade_sAgVIjhN']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-01-15 00:00:00', '2018-01-15 00:00:00', '300290', None, -1, 8.08, 8.08, 'trade_success', 1000.0, 1000.0, 8097.12, 0, 'Order_XAcLutCp', 'Trade_0yJSEspU']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-01-15 00:00:00', '2018-01-15 00:00:00', '600198', None, -1, 10.61, 10.61, 'trade_success', 1000.0, 1000.0, 10630.915, 0, 'Order_VXd1B3KE', 'Trade_js8PH6Qm']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-01-16 00:00:00', '2018-01-16 00:00:00', '000063', None, 1, 38.6, 38.6, 'trade_success', 1000, 1000, 38609.65, 0, 'Order_xfhHbnI0', 'Trade_tlUAkHiP']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-01-16 00:00:00', '2018-01-16 00:00:00', '002544', None, -1, 14.62, 14.620000000000001, 'trade_success', 1000.0, 1000.0, 14646.930000000002, 0, 'Order_ydeshXSg', 'Trade_8bSmdCun']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-01-16 00:00:00', '2018-01-16 00:00:00', '600718', None, -1, 14.27, 14.265, 'trade_success', 1000.0, 1000.0, 14291.3975, 0, 'Order_tWCmXwzc', 'Trade_s8WC0ZnE']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-01-16 00:00:00', '2018-01-16 00:00:00', '600804', None, -1, 16.51, 16.509999999999998, 'trade_success', 1000.0, 1000.0, 16539.764999999996, 0, 'Order_tZncUvNb', 'Trade_iHCjvwFs']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-01-17 00:00:00', '2018-01-17 00:00:00', '300297', None, 1, 9.56, 9.56, 'trade_success', 1000, 1000, 9565.0, 0, 'Order_X3FLjoUW', 'Trade_F7kfPS4g']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-01-19 00:00:00', '2018-01-19 00:00:00', '000063', None, -1, 36.86, 36.864999999999995, 'trade_success', 1000.0, 1000.0, 36929.51374999999, 0, 'Order_gwUSRf3G', 'Trade_Tdzf9kvy']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-01-19 00:00:00', '2018-01-19 00:00:00', '002279', None, 1, 10.33, 10.33, 'trade_success', 1000, 1000, 10335.0, 0, 'Order_nuivkPTW', 'Trade_We5QaM0s']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-01-19 00:00:00', '2018-01-19 00:00:00', '300287', None, 1, 7.46, 7.46, 'trade_success', 1000, 1000, 7465.0, 0, 'Order_cnYqAs83', 'Trade_gPDUy2h3']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-01-19 00:00:00', '2018-01-19 00:00:00', '600804', None, 1, 17.22, 17.22, 'trade_success', 1000, 1000, 17225.0, 0, 'Order_YnjQZoGq', 'Trade_6iUDtjIE']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-01-22 00:00:00', '2018-01-22 00:00:00', '002095', None, 1, 38.61, 38.61, 'trade_success', 1000, 1000, 38619.6525, 0, 'Order_HwfdWtuv', 'Trade_HLw8iGBj']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-01-22 00:00:00', '2018-01-22 00:00:00', '300044', None, 1, 8.7, 8.6992327066, 'trade_success', 1000, 1000, 8704.2327066, 0, 'Order_ZdF4RoQu', 'Trade_6MDqYXtu']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-01-22 00:00:00', '2018-01-22 00:00:00', '300128', None, 1, 10.18, 10.18, 'trade_success', 1000, 1000, 10185.0, 0, 'Order_EKocg1CZ', 'Trade_BuFwXT5E']\n",
      "receive deal\n",
      "5570.342500000026\n",
      "NOT ENOUGH MONEY FOR Order_EKocg1CZ\n",
      "['JCSC_EXAMPLE', '2018-01-22 00:00:00', '2018-01-22 00:00:00', '300245', None, 1, 13.76, 13.76, 'trade_success', 1000, 1000, 13765.0, 0, 'Order_UXAnbpHf', 'Trade_dY9t8JWl']\n",
      "receive deal\n",
      "5570.342500000026\n",
      "NOT ENOUGH MONEY FOR Order_UXAnbpHf\n",
      "['JCSC_EXAMPLE', '2018-01-23 00:00:00', '2018-01-23 00:00:00', '000100', None, -1, 3.85, 3.8499999999999996, 'trade_success', 1000.0, 1000.0, 3860.7749999999996, 0, 'Order_kBXqtsld', 'Trade_XH45AK7z']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-01-23 00:00:00', '2018-01-23 00:00:00', '002544', None, 1, 14.93, 14.93, 'trade_success', 1000, 1000, 14935.0, 0, 'Order_ZUJxEzIS', 'Trade_tv7pMK8f']\n",
      "receive deal\n",
      "9427.080000000027\n",
      "NOT ENOUGH MONEY FOR Order_ZUJxEzIS\n",
      "['JCSC_EXAMPLE', '2018-01-23 00:00:00', '2018-01-23 00:00:00', '002837', None, 1, 20.19, 20.1899406798, 'trade_success', 1000, 1000, 20194.98816496995, 0, 'Order_nXgWdPKS', 'Trade_pKtkd1Be']\n",
      "receive deal\n",
      "9427.080000000027\n",
      "NOT ENOUGH MONEY FOR Order_nXgWdPKS\n",
      "['JCSC_EXAMPLE', '2018-01-23 00:00:00', '2018-01-23 00:00:00', '300052', None, -1, 14.38, 14.385, 'trade_success', 1000.0, 1000.0, 14411.5775, 0, 'Order_XNxl7tUP', 'Trade_SWDpNVug']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-01-23 00:00:00', '2018-01-23 00:00:00', '300113', None, 1, 18.38, 18.38, 'trade_success', 1000, 1000, 18385.0, 0, 'Order_AI1Fh2zM', 'Trade_4YyNbElL']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-01-23 00:00:00', '2018-01-23 00:00:00', '300271', None, 1, 15.65, 15.65, 'trade_success', 1000, 1000, 15655.0, 0, 'Order_68oVRP2Z', 'Trade_8ZElLORp']\n",
      "receive deal\n",
      "5420.080000000027\n",
      "NOT ENOUGH MONEY FOR Order_68oVRP2Z\n",
      "['JCSC_EXAMPLE', '2018-01-23 00:00:00', '2018-01-23 00:00:00', '300366', None, 1, 11.89, 11.89, 'trade_success', 1000, 1000, 11895.0, 0, 'Order_wQ1IgfYC', 'Trade_pAkV8DOB']\n",
      "receive deal\n",
      "5420.080000000027\n",
      "NOT ENOUGH MONEY FOR Order_wQ1IgfYC\n",
      "['JCSC_EXAMPLE', '2018-01-23 00:00:00', '2018-01-23 00:00:00', '600588', None, 1, 17.07, 17.0685466831, 'trade_success', 1000, 1000, 17073.546683099998, 0, 'Order_RsOx3Yz6', 'Trade_qYkHoFO1']\n",
      "receive deal\n",
      "5420.080000000027\n",
      "NOT ENOUGH MONEY FOR Order_RsOx3Yz6\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['JCSC_EXAMPLE', '2018-01-23 00:00:00', '2018-01-23 00:00:00', '600797', None, -1, 12.25, 12.25, 'trade_success', 1000.0, 1000.0, 12273.375, 0, 'Order_1HcuVpjx', 'Trade_Fso2LJax']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-01-24 00:00:00', '2018-01-24 00:00:00', '000066', None, 1, 7.16, 7.16, 'trade_success', 1000, 1000, 7165.0, 0, 'Order_zp0JfaoD', 'Trade_qfxuYiHW']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-01-24 00:00:00', '2018-01-24 00:00:00', '000836', None, 1, 5.28, 5.28, 'trade_success', 1000, 1000, 5285.0, 0, 'Order_F6Pwb7Do', 'Trade_qV5j6vtw']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-01-24 00:00:00', '2018-01-24 00:00:00', '002268', None, 1, 23.6, 23.6, 'trade_success', 1000, 1000, 23605.9, 0, 'Order_cMeJrbuY', 'Trade_PGTxUoaf']\n",
      "receive deal\n",
      "5229.747500000029\n",
      "NOT ENOUGH MONEY FOR Order_cMeJrbuY\n",
      "['JCSC_EXAMPLE', '2018-01-24 00:00:00', '2018-01-24 00:00:00', '300036', None, 1, 15.46, 15.4591896377, 'trade_success', 1000, 1000, 15464.1896377, 0, 'Order_eXRzb7at', 'Trade_cfHJG5ut']\n",
      "receive deal\n",
      "5229.747500000029\n",
      "NOT ENOUGH MONEY FOR Order_eXRzb7at\n",
      "['JCSC_EXAMPLE', '2018-01-24 00:00:00', '2018-01-24 00:00:00', '300052', None, 1, 15.21, 15.21, 'trade_success', 1000, 1000, 15215.0, 0, 'Order_UHZ67ecd', 'Trade_dJxAFVZo']\n",
      "receive deal\n",
      "5229.747500000029\n",
      "NOT ENOUGH MONEY FOR Order_UHZ67ecd\n",
      "['JCSC_EXAMPLE', '2018-01-24 00:00:00', '2018-01-24 00:00:00', '300128', None, 1, 10.17, 10.17, 'trade_success', 1000, 1000, 10175.0, 0, 'Order_hVp8SwyO', 'Trade_mxVi1qsp']\n",
      "receive deal\n",
      "5229.747500000029\n",
      "NOT ENOUGH MONEY FOR Order_hVp8SwyO\n",
      "['JCSC_EXAMPLE', '2018-01-24 00:00:00', '2018-01-24 00:00:00', '300168', None, 1, 14.0, 14.0, 'trade_success', 1000, 1000, 14005.0, 0, 'Order_4xXLFEr0', 'Trade_tu6VRxOG']\n",
      "receive deal\n",
      "5229.747500000029\n",
      "NOT ENOUGH MONEY FOR Order_4xXLFEr0\n",
      "['JCSC_EXAMPLE', '2018-01-24 00:00:00', '2018-01-24 00:00:00', '300274', None, 1, 17.62, 17.62, 'trade_success', 1000, 1000, 17625.0, 0, 'Order_I06MnKcb', 'Trade_LgBXO8Hi']\n",
      "receive deal\n",
      "5229.747500000029\n",
      "NOT ENOUGH MONEY FOR Order_I06MnKcb\n",
      "['JCSC_EXAMPLE', '2018-01-24 00:00:00', '2018-01-24 00:00:00', '300290', None, 1, 8.18, 8.18, 'trade_success', 1000, 1000, 8185.0, 0, 'Order_1G3TE0b7', 'Trade_pHUaNL6r']\n",
      "receive deal\n",
      "5229.747500000029\n",
      "NOT ENOUGH MONEY FOR Order_1G3TE0b7\n",
      "['JCSC_EXAMPLE', '2018-01-24 00:00:00', '2018-01-24 00:00:00', '300311', None, 1, 13.79, 13.79, 'trade_success', 1000, 1000, 13795.0, 0, 'Order_OgsRFrGz', 'Trade_SmOrTXf1']\n",
      "receive deal\n",
      "5229.747500000029\n",
      "NOT ENOUGH MONEY FOR Order_OgsRFrGz\n",
      "['JCSC_EXAMPLE', '2018-01-24 00:00:00', '2018-01-24 00:00:00', '300367', None, 1, 15.05, 15.05, 'trade_success', 1000, 1000, 15055.0, 0, 'Order_vwMXzSDN', 'Trade_8ej4JzNX']\n",
      "receive deal\n",
      "5229.747500000029\n",
      "NOT ENOUGH MONEY FOR Order_vwMXzSDN\n",
      "['JCSC_EXAMPLE', '2018-01-24 00:00:00', '2018-01-24 00:00:00', '600756', None, 1, 18.1, 18.1, 'trade_success', 1000, 1000, 18105.0, 0, 'Order_o7lWmRqf', 'Trade_ZWhdNvs5']\n",
      "receive deal\n",
      "5229.747500000029\n",
      "NOT ENOUGH MONEY FOR Order_o7lWmRqf\n",
      "['JCSC_EXAMPLE', '2018-01-24 00:00:00', '2018-01-24 00:00:00', '600797', None, 1, 12.47, 12.47, 'trade_success', 1000, 1000, 12475.0, 0, 'Order_ieymZrfR', 'Trade_yeRhTrM8']\n",
      "receive deal\n",
      "5229.747500000029\n",
      "NOT ENOUGH MONEY FOR Order_ieymZrfR\n",
      "['JCSC_EXAMPLE', '2018-01-24 00:00:00', '2018-01-24 00:00:00', '600845', None, 1, 20.26, 20.2595054213, 'trade_success', 1000, 1000, 20264.570297655322, 0, 'Order_FwW62ukI', 'Trade_ba4k60gM']\n",
      "receive deal\n",
      "5229.747500000029\n",
      "NOT ENOUGH MONEY FOR Order_FwW62ukI\n",
      "['JCSC_EXAMPLE', '2018-01-24 00:00:00', '2018-01-24 00:00:00', '603019', None, 1, 41.0, 41.001722561, 'trade_success', 1000, 1000, 41011.97299164025, 0, 'Order_hZdOCNnb', 'Trade_ULS53lJc']\n",
      "receive deal\n",
      "5229.747500000029\n",
      "NOT ENOUGH MONEY FOR Order_hZdOCNnb\n",
      "['JCSC_EXAMPLE', '2018-01-25 00:00:00', '2018-01-25 00:00:00', '002439', None, 1, 21.79, 21.7932734275, 'trade_success', 1000, 1000, 21798.721745856874, 0, 'Order_CuTdlAYW', 'Trade_SuVIcXlD']\n",
      "receive deal\n",
      "5229.747500000029\n",
      "NOT ENOUGH MONEY FOR Order_CuTdlAYW\n",
      "['JCSC_EXAMPLE', '2018-01-25 00:00:00', '2018-01-25 00:00:00', '300025', None, 1, 5.95, 5.95, 'trade_success', 1000, 1000, 5955.0, 0, 'Order_EWnVByGR', 'Trade_RdwlPEBs']\n",
      "receive deal\n",
      "5229.747500000029\n",
      "NOT ENOUGH MONEY FOR Order_EWnVByGR\n",
      "['JCSC_EXAMPLE', '2018-01-25 00:00:00', '2018-01-25 00:00:00', '300212', None, 1, 28.28, 28.28, 'trade_success', 1000, 1000, 28287.07, 0, 'Order_wF97idvM', 'Trade_rGUcoMzF']\n",
      "receive deal\n",
      "5229.747500000029\n",
      "NOT ENOUGH MONEY FOR Order_wF97idvM\n",
      "['JCSC_EXAMPLE', '2018-01-25 00:00:00', '2018-01-25 00:00:00', '300431', None, 1, 24.77, 24.77, 'trade_success', 1000, 1000, 24776.1925, 0, 'Order_fpiLkNw4', 'Trade_1Xn7UVtj']\n",
      "receive deal\n",
      "5229.747500000029\n",
      "NOT ENOUGH MONEY FOR Order_fpiLkNw4\n",
      "['JCSC_EXAMPLE', '2018-01-25 00:00:00', '2018-01-25 00:00:00', '600198', None, 1, 10.36, 10.36, 'trade_success', 1000, 1000, 10365.0, 0, 'Order_gcuTbVzX', 'Trade_l3wL97o0']\n",
      "receive deal\n",
      "5229.747500000029\n",
      "NOT ENOUGH MONEY FOR Order_gcuTbVzX\n",
      "['JCSC_EXAMPLE', '2018-01-25 00:00:00', '2018-01-25 00:00:00', '600225', None, 1, 5.02, 5.02, 'trade_success', 1000, 1000, 5025.0, 0, 'Order_MiJZy6Kd', 'Trade_XoudiA5J']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-01-25 00:00:00', '2018-01-25 00:00:00', '600590', None, 1, 10.37, 10.37, 'trade_success', 1000, 1000, 10375.0, 0, 'Order_Q4t7WriC', 'Trade_YSV41wTf']\n",
      "receive deal\n",
      "200.96250000002874\n",
      "NOT ENOUGH MONEY FOR Order_Q4t7WriC\n",
      "['JCSC_EXAMPLE', '2018-01-26 00:00:00', '2018-01-26 00:00:00', '002368', None, 1, 23.35, 23.35, 'trade_success', 1000, 1000, 23355.8375, 0, 'Order_zBZtUkXs', 'Trade_nKQPowgY']\n",
      "receive deal\n",
      "200.96250000002874\n",
      "NOT ENOUGH MONEY FOR Order_zBZtUkXs\n",
      "['JCSC_EXAMPLE', '2018-01-26 00:00:00', '2018-01-26 00:00:00', '300051', None, 1, 11.04, 11.04, 'trade_success', 1000, 1000, 11045.0, 0, 'Order_kx3Gd7fz', 'Trade_s5zJQo4T']\n",
      "receive deal\n",
      "200.96250000002874\n",
      "NOT ENOUGH MONEY FOR Order_kx3Gd7fz\n",
      "['JCSC_EXAMPLE', '2018-01-26 00:00:00', '2018-01-26 00:00:00', '300188', None, 1, 20.49, 20.49, 'trade_success', 1000, 1000, 20495.1225, 0, 'Order_hjF4uOLe', 'Trade_B54JK9u8']\n",
      "receive deal\n",
      "200.96250000002874\n",
      "NOT ENOUGH MONEY FOR Order_hjF4uOLe\n",
      "['JCSC_EXAMPLE', '2018-01-26 00:00:00', '2018-01-26 00:00:00', '300229', None, 1, 14.04, 14.04, 'trade_success', 1000, 1000, 14045.0, 0, 'Order_y7COnJAD', 'Trade_9o6gy5xO']\n",
      "receive deal\n",
      "200.96250000002874\n",
      "NOT ENOUGH MONEY FOR Order_y7COnJAD\n",
      "['JCSC_EXAMPLE', '2018-01-26 00:00:00', '2018-01-26 00:00:00', '600289', None, 1, 5.04, 5.04, 'trade_success', 1000, 1000, 5045.0, 0, 'Order_xsChFO5l', 'Trade_0EjuJTWK']\n",
      "receive deal\n",
      "200.96250000002874\n",
      "NOT ENOUGH MONEY FOR Order_xsChFO5l\n",
      "['JCSC_EXAMPLE', '2018-01-26 00:00:00', '2018-01-26 00:00:00', '600601', None, 1, 3.6, 3.6, 'trade_success', 1000, 1000, 3605.0, 0, 'Order_8SpIK4jr', 'Trade_Uz3gOxqo']\n",
      "receive deal\n",
      "200.96250000002874\n",
      "NOT ENOUGH MONEY FOR Order_8SpIK4jr\n",
      "['JCSC_EXAMPLE', '2018-01-29 00:00:00', '2018-01-29 00:00:00', '002301', None, 1, 17.73, 17.73, 'trade_success', 1000, 1000, 17735.0, 0, 'Order_agb6Edmv', 'Trade_BIiCc8kp']\n",
      "receive deal\n",
      "200.96250000002874\n",
      "NOT ENOUGH MONEY FOR Order_agb6Edmv\n",
      "['JCSC_EXAMPLE', '2018-01-29 00:00:00', '2018-01-29 00:00:00', '300078', None, 1, 9.78, 9.78, 'trade_success', 1000, 1000, 9785.0, 0, 'Order_bcCn5VLi', 'Trade_ELhv0riR']\n",
      "receive deal\n",
      "200.96250000002874\n",
      "NOT ENOUGH MONEY FOR Order_bcCn5VLi\n",
      "['JCSC_EXAMPLE', '2018-01-29 00:00:00', '2018-01-29 00:00:00', '600225', None, -1, 4.91, 4.91, 'trade_success', 1000.0, 1000.0, 4922.365, 0, 'Order_AX0rzfGI', 'Trade_kiB9Z5tl']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-01-29 00:00:00', '2018-01-29 00:00:00', '600410', None, 1, 9.99, 9.99, 'trade_success', 1000, 1000, 9995.0, 0, 'Order_fBXQb2KP', 'Trade_TO3ClHAP']\n",
      "receive deal\n",
      "5119.5550000000285\n",
      "NOT ENOUGH MONEY FOR Order_fBXQb2KP\n",
      "['JCSC_EXAMPLE', '2018-01-29 00:00:00', '2018-01-29 00:00:00', '600767', None, 1, 6.1, 6.1, 'trade_success', 1000, 1000, 6105.0, 0, 'Order_cEulL6DY', 'Trade_orfSG0aI']\n",
      "receive deal\n",
      "5119.5550000000285\n",
      "NOT ENOUGH MONEY FOR Order_cEulL6DY\n",
      "['JCSC_EXAMPLE', '2018-01-30 00:00:00', '2018-01-30 00:00:00', '300608', None, 1, 30.89, 30.89, 'trade_success', 1000, 1000, 30897.7225, 0, 'Order_MUjbiCNu', 'Trade_IEkVehYq']\n",
      "receive deal\n",
      "5119.5550000000285\n",
      "NOT ENOUGH MONEY FOR Order_MUjbiCNu\n",
      "['JCSC_EXAMPLE', '2018-01-31 00:00:00', '2018-01-31 00:00:00', '000070', None, -1, 9.45, 9.45, 'trade_success', 1000.0, 1000.0, 9469.175, 0, 'Order_vWTuR1dJ', 'Trade_6jc4o0sb']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-01-31 00:00:00', '2018-01-31 00:00:00', '002065', None, -1, 7.99, 7.99, 'trade_success', 1000.0, 1000.0, 8006.985, 0, 'Order_zL7NDg80', 'Trade_Q7unAJi6']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-01-31 00:00:00', '2018-01-31 00:00:00', '002195', None, -1, 6.16, 6.164999999999999, 'trade_success', 1000.0, 1000.0, 6179.2474999999995, 0, 'Order_4Fqt9iZU', 'Trade_pRkdrVDx']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-01-31 00:00:00', '2018-01-31 00:00:00', '002335', None, -1, 28.81, 28.8137193049, 'trade_success', 1000.0, 1000.0, 28864.143313683577, 0, 'Order_YpHiZrwc', 'Trade_nmazIO9W']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-01-31 00:00:00', '2018-01-31 00:00:00', '002396', None, 1, 19.67, 19.67, 'trade_success', 1000, 1000, 19675.0, 0, 'Order_pQWZ5ga3', 'Trade_6NHP27KW']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-02-01 00:00:00', '2018-02-01 00:00:00', '000066', None, -1, 6.9, 6.9, 'trade_success', 1000.0, 1000.0, 6915.35, 0, 'Order_RLMTWSVJ', 'Trade_lVvdr1B7']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-02-01 00:00:00', '2018-02-01 00:00:00', '002279', None, -1, 10.25, 10.25, 'trade_success', 1000.0, 1000.0, 10270.375, 0, 'Order_c7m3wzsn', 'Trade_TjmvpHkY']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-02-01 00:00:00', '2018-02-01 00:00:00', '002396', None, -1, 19.21, 19.215, 'trade_success', 1000.0, 1000.0, 19248.8225, 0, 'Order_90T1utfI', 'Trade_nc3UNVre']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-02-01 00:00:00', '2018-02-01 00:00:00', '300297', None, -1, 9.22, 9.225, 'trade_success', 1000.0, 1000.0, 9243.8375, 0, 'Order_34YJcEK1', 'Trade_Uv4X5z8d']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-02-01 00:00:00', '2018-02-01 00:00:00', '600105', None, -1, 6.15, 6.154999999999999, 'trade_success', 1000.0, 1000.0, 6169.232499999999, 0, 'Order_Rax4OMJS', 'Trade_5EMAi2CV']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-02-01 00:00:00', '2018-02-01 00:00:00', '600804', None, -1, 16.0, 15.995000000000001, 'trade_success', 1000.0, 1000.0, 16023.992500000002, 0, 'Order_pibUeJjF', 'Trade_zL862Gkh']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-02-02 00:00:00', '2018-02-02 00:00:00', '002456', None, 1, 19.15, 19.15, 'trade_success', 1000, 1000, 19155.0, 0, 'Order_oil2d4FY', 'Trade_VfrMGApi']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-02-02 00:00:00', '2018-02-02 00:00:00', '601360', None, 1, 55.03, 55.03, 'trade_success', 1000, 1000, 55043.7575, 0, 'Order_FkBz4LUj', 'Trade_6LrFKkw2']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-02-06 00:00:00', '2018-02-06 00:00:00', '000836', None, -1, 4.98, 4.98, 'trade_success', 1000.0, 1000.0, 4992.47, 0, 'Order_5pNM1od2', 'Trade_GKknWqF4']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-02-06 00:00:00', '2018-02-06 00:00:00', '002095', None, -1, 39.09, 39.095, 'trade_success', 1000.0, 1000.0, 39163.41625, 0, 'Order_reqHsSf1', 'Trade_zEyPQcXq']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-02-07 00:00:00', '2018-02-07 00:00:00', '002837', None, 1, 19.02, 19.0234107738, 'trade_success', 1000, 1000, 19028.4107738, 0, 'Order_vRcUK6wf', 'Trade_iWKUvwmk']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-02-08 00:00:00', '2018-02-08 00:00:00', '300431', None, 1, 25.19, 25.19, 'trade_success', 1000, 1000, 25196.2975, 0, 'Order_9HYI4rUk', 'Trade_nKrPCZI8']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-02-12 00:00:00', '2018-02-12 00:00:00', '000977', None, 1, 16.33, 16.3317809396, 'trade_success', 1000, 1000, 16336.780939600001, 0, 'Order_RuDxbP4f', 'Trade_l3iF5HNU']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-02-12 00:00:00', '2018-02-12 00:00:00', '002279', None, 1, 10.72, 10.72, 'trade_success', 1000, 1000, 10725.0, 0, 'Order_qSj7wEBG', 'Trade_0Gv5cD4T']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-02-12 00:00:00', '2018-02-12 00:00:00', '002417', None, 1, 10.53, 10.53, 'trade_success', 1000, 1000, 10535.0, 0, 'Order_hd7mraxC', 'Trade_cSj9DNVf']\n",
      "receive deal\n",
      "4217.9800000000105\n",
      "NOT ENOUGH MONEY FOR Order_hd7mraxC\n",
      "['JCSC_EXAMPLE', '2018-02-12 00:00:00', '2018-02-12 00:00:00', '002439', None, 1, 21.11, 21.1147282841, 'trade_success', 1000, 1000, 21120.006966171026, 0, 'Order_Uw4Takro', 'Trade_njbqYfxp']\n",
      "receive deal\n",
      "4217.9800000000105\n",
      "NOT ENOUGH MONEY FOR Order_Uw4Takro\n",
      "['JCSC_EXAMPLE', '2018-02-12 00:00:00', '2018-02-12 00:00:00', '002463', None, 1, 4.41, 4.4104444444, 'trade_success', 1000, 1000, 4415.4444444, 0, 'Order_M7ZeGdiX', 'Trade_LbIHZ0lk']\n",
      "receive deal\n",
      "4217.9800000000105\n",
      "NOT ENOUGH MONEY FOR Order_M7ZeGdiX\n",
      "['JCSC_EXAMPLE', '2018-02-12 00:00:00', '2018-02-12 00:00:00', '300188', None, 1, 21.28, 21.28, 'trade_success', 1000, 1000, 21285.32, 0, 'Order_P5BALnxJ', 'Trade_H8hG6jvm']\n",
      "receive deal\n",
      "4217.9800000000105\n",
      "NOT ENOUGH MONEY FOR Order_P5BALnxJ\n",
      "['JCSC_EXAMPLE', '2018-02-12 00:00:00', '2018-02-12 00:00:00', '600845', None, 1, 21.32, 21.3237013369, 'trade_success', 1000, 1000, 21329.03226223423, 0, 'Order_vjAIk6d0', 'Trade_ZpO1VnAz']\n",
      "receive deal\n",
      "4217.9800000000105\n",
      "NOT ENOUGH MONEY FOR Order_vjAIk6d0\n",
      "['JCSC_EXAMPLE', '2018-02-13 00:00:00', '2018-02-13 00:00:00', '002368', None, 1, 21.39, 21.39, 'trade_success', 1000, 1000, 21395.3475, 0, 'Order_mfbnFLeK', 'Trade_rmakF2AC']\n",
      "receive deal\n",
      "4217.9800000000105\n",
      "NOT ENOUGH MONEY FOR Order_mfbnFLeK\n",
      "['JCSC_EXAMPLE', '2018-02-13 00:00:00', '2018-02-13 00:00:00', '002396', None, 1, 18.96, 18.96, 'trade_success', 1000, 1000, 18965.0, 0, 'Order_GkTcypIz', 'Trade_Y9CMz2iH']\n",
      "receive deal\n",
      "4217.9800000000105\n",
      "NOT ENOUGH MONEY FOR Order_GkTcypIz\n",
      "['JCSC_EXAMPLE', '2018-02-13 00:00:00', '2018-02-13 00:00:00', '600522', None, 1, 11.76, 11.76, 'trade_success', 1000, 1000, 11765.0, 0, 'Order_e7F4KZ0d', 'Trade_GpcPjDuL']\n",
      "receive deal\n",
      "4217.9800000000105\n",
      "NOT ENOUGH MONEY FOR Order_e7F4KZ0d\n",
      "['JCSC_EXAMPLE', '2018-02-14 00:00:00', '2018-02-14 00:00:00', '000611', None, 1, 6.73, 6.73, 'trade_success', 1000, 1000, 6735.0, 0, 'Order_mNGk19ID', 'Trade_ZNBngDdi']\n",
      "receive deal\n",
      "4217.9800000000105\n",
      "NOT ENOUGH MONEY FOR Order_mNGk19ID\n",
      "['JCSC_EXAMPLE', '2018-02-14 00:00:00', '2018-02-14 00:00:00', '300271', None, 1, 16.63, 16.63, 'trade_success', 1000, 1000, 16635.0, 0, 'Order_ISF6yXYl', 'Trade_uFViW3Gw']\n",
      "receive deal\n",
      "4217.9800000000105\n",
      "NOT ENOUGH MONEY FOR Order_ISF6yXYl\n",
      "['JCSC_EXAMPLE', '2018-02-14 00:00:00', '2018-02-14 00:00:00', '600100', None, 1, 9.79, 9.79, 'trade_success', 1000, 1000, 9795.0, 0, 'Order_xk1OmeNV', 'Trade_JlX6E8s5']\n",
      "receive deal\n",
      "4217.9800000000105\n",
      "NOT ENOUGH MONEY FOR Order_xk1OmeNV\n",
      "['JCSC_EXAMPLE', '2018-02-14 00:00:00', '2018-02-14 00:00:00', '603019', None, 1, 37.63, 37.6281631098, 'trade_success', 1000, 1000, 37637.57015057745, 0, 'Order_8hrBKiuW', 'Trade_EogLGT8P']\n",
      "receive deal\n",
      "4217.9800000000105\n",
      "NOT ENOUGH MONEY FOR Order_8hrBKiuW\n",
      "['JCSC_EXAMPLE', '2018-02-22 00:00:00', '2018-02-22 00:00:00', '000063', None, 1, 31.22, 31.22, 'trade_success', 1000, 1000, 31227.805, 0, 'Order_ZHVGeAzq', 'Trade_V3gMaSmp']\n",
      "receive deal\n",
      "4217.9800000000105\n",
      "NOT ENOUGH MONEY FOR Order_ZHVGeAzq\n",
      "['JCSC_EXAMPLE', '2018-02-22 00:00:00', '2018-02-22 00:00:00', '000100', None, 1, 3.47, 3.47, 'trade_success', 1000, 1000, 3475.0, 0, 'Order_lMFpQKBZ', 'Trade_XiEvb8O5']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-02-22 00:00:00', '2018-02-22 00:00:00', '000938', None, 1, 59.38, 59.38, 'trade_success', 1000, 1000, 59394.845, 0, 'Order_nF7cCPua', 'Trade_o7glfAFY']\n",
      "receive deal\n",
      "741.9075000000103\n",
      "NOT ENOUGH MONEY FOR Order_nF7cCPua\n",
      "['JCSC_EXAMPLE', '2018-02-22 00:00:00', '2018-02-22 00:00:00', '002268', None, 1, 23.43, 23.43, 'trade_success', 1000, 1000, 23435.8575, 0, 'Order_UZF0BmHf', 'Trade_oXSQBaWD']\n",
      "receive deal\n",
      "741.9075000000103\n",
      "NOT ENOUGH MONEY FOR Order_UZF0BmHf\n",
      "['JCSC_EXAMPLE', '2018-02-22 00:00:00', '2018-02-22 00:00:00', '002281', None, 1, 23.85, 23.85, 'trade_success', 1000, 1000, 23855.9625, 0, 'Order_o74bfcqN', 'Trade_0VkneSzp']\n",
      "receive deal\n",
      "741.9075000000103\n",
      "NOT ENOUGH MONEY FOR Order_o74bfcqN\n",
      "['JCSC_EXAMPLE', '2018-02-22 00:00:00', '2018-02-22 00:00:00', '002415', None, 1, 40.44, 40.44, 'trade_success', 1000, 1000, 40450.11, 0, 'Order_YcvtIjLb', 'Trade_TJaBmYRC']\n",
      "receive deal\n",
      "741.9075000000103\n",
      "NOT ENOUGH MONEY FOR Order_YcvtIjLb\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['JCSC_EXAMPLE', '2018-02-22 00:00:00', '2018-02-22 00:00:00', '002642', None, 1, 10.67, 10.67, 'trade_success', 1000, 1000, 10675.0, 0, 'Order_zLProkqZ', 'Trade_ZRDUd6th']\n",
      "receive deal\n",
      "741.9075000000103\n",
      "NOT ENOUGH MONEY FOR Order_zLProkqZ\n",
      "['JCSC_EXAMPLE', '2018-02-22 00:00:00', '2018-02-22 00:00:00', '300036', None, 1, 13.75, 13.7470321247, 'trade_success', 1000, 1000, 13752.032124700001, 0, 'Order_mc9blrYv', 'Trade_nE6HODV1']\n",
      "receive deal\n",
      "741.9075000000103\n",
      "NOT ENOUGH MONEY FOR Order_mc9blrYv\n",
      "['JCSC_EXAMPLE', '2018-02-22 00:00:00', '2018-02-22 00:00:00', '300078', None, 1, 8.3, 8.3, 'trade_success', 1000, 1000, 8305.0, 0, 'Order_g1z5AZUW', 'Trade_AMEVfKTc']\n",
      "receive deal\n",
      "741.9075000000103\n",
      "NOT ENOUGH MONEY FOR Order_g1z5AZUW\n",
      "['JCSC_EXAMPLE', '2018-02-22 00:00:00', '2018-02-22 00:00:00', '300229', None, 1, 12.36, 12.36, 'trade_success', 1000, 1000, 12365.0, 0, 'Order_dIQtrTWz', 'Trade_FhtGNMuq']\n",
      "receive deal\n",
      "741.9075000000103\n",
      "NOT ENOUGH MONEY FOR Order_dIQtrTWz\n",
      "['JCSC_EXAMPLE', '2018-02-22 00:00:00', '2018-02-22 00:00:00', '300311', None, 1, 12.4, 12.4, 'trade_success', 1000, 1000, 12405.0, 0, 'Order_RHANTVEZ', 'Trade_koV3Q9fh']\n",
      "receive deal\n",
      "741.9075000000103\n",
      "NOT ENOUGH MONEY FOR Order_RHANTVEZ\n",
      "['JCSC_EXAMPLE', '2018-02-22 00:00:00', '2018-02-22 00:00:00', '300367', None, 1, 14.1, 14.1, 'trade_success', 1000, 1000, 14105.0, 0, 'Order_pnYv9Fk2', 'Trade_f6nKGTON']\n",
      "receive deal\n",
      "741.9075000000103\n",
      "NOT ENOUGH MONEY FOR Order_pnYv9Fk2\n",
      "['JCSC_EXAMPLE', '2018-02-22 00:00:00', '2018-02-22 00:00:00', '600385', None, 1, 10.24, 10.24, 'trade_success', 1000, 1000, 10245.0, 0, 'Order_JypLiQHK', 'Trade_qoT7WCGw']\n",
      "receive deal\n",
      "741.9075000000103\n",
      "NOT ENOUGH MONEY FOR Order_JypLiQHK\n",
      "['JCSC_EXAMPLE', '2018-02-22 00:00:00', '2018-02-22 00:00:00', '600410', None, 1, 9.47, 9.47, 'trade_success', 1000, 1000, 9475.0, 0, 'Order_eHE2XPsm', 'Trade_qlC3hNup']\n",
      "receive deal\n",
      "741.9075000000103\n",
      "NOT ENOUGH MONEY FOR Order_eHE2XPsm\n",
      "['JCSC_EXAMPLE', '2018-02-22 00:00:00', '2018-02-22 00:00:00', '600718', None, 1, 12.26, 12.26, 'trade_success', 1000, 1000, 12265.0, 0, 'Order_vurKnY0P', 'Trade_lJHYKIA9']\n",
      "receive deal\n",
      "741.9075000000103\n",
      "NOT ENOUGH MONEY FOR Order_vurKnY0P\n",
      "['JCSC_EXAMPLE', '2018-02-22 00:00:00', '2018-02-22 00:00:00', '600728', None, 1, 6.99, 6.9869554611, 'trade_success', 1000, 1000, 6991.9554611, 0, 'Order_p1NKloFq', 'Trade_nDmJU19M']\n",
      "receive deal\n",
      "741.9075000000103\n",
      "NOT ENOUGH MONEY FOR Order_p1NKloFq\n",
      "['JCSC_EXAMPLE', '2018-02-22 00:00:00', '2018-02-22 00:00:00', '600850', None, 1, 15.07, 15.07, 'trade_success', 1000, 1000, 15075.0, 0, 'Order_gFqlSkUx', 'Trade_y1xtjrlh']\n",
      "receive deal\n",
      "741.9075000000103\n",
      "NOT ENOUGH MONEY FOR Order_gFqlSkUx\n",
      "['JCSC_EXAMPLE', '2018-02-23 00:00:00', '2018-02-23 00:00:00', '000555', None, 1, 9.86, 9.86, 'trade_success', 1000, 1000, 9865.0, 0, 'Order_gt75fZy1', 'Trade_e0dqykJK']\n",
      "receive deal\n",
      "741.9075000000103\n",
      "NOT ENOUGH MONEY FOR Order_gt75fZy1\n",
      "['JCSC_EXAMPLE', '2018-02-23 00:00:00', '2018-02-23 00:00:00', '002093', None, 1, 8.63, 8.63, 'trade_success', 1000, 1000, 8635.0, 0, 'Order_1qSUIEb5', 'Trade_jDFxdRqi']\n",
      "receive deal\n",
      "741.9075000000103\n",
      "NOT ENOUGH MONEY FOR Order_1qSUIEb5\n",
      "['JCSC_EXAMPLE', '2018-02-23 00:00:00', '2018-02-23 00:00:00', '002197', None, 1, 10.28, 10.28, 'trade_success', 1000, 1000, 10285.0, 0, 'Order_EOebV2mG', 'Trade_gjJHWOym']\n",
      "receive deal\n",
      "741.9075000000103\n",
      "NOT ENOUGH MONEY FOR Order_EOebV2mG\n",
      "['JCSC_EXAMPLE', '2018-02-23 00:00:00', '2018-02-23 00:00:00', '300002', None, 1, 6.34, 6.34, 'trade_success', 1000, 1000, 6345.0, 0, 'Order_iTyCd5nP', 'Trade_1WKxzLwY']\n",
      "receive deal\n",
      "741.9075000000103\n",
      "NOT ENOUGH MONEY FOR Order_iTyCd5nP\n",
      "['JCSC_EXAMPLE', '2018-02-23 00:00:00', '2018-02-23 00:00:00', '300025', None, 1, 4.77, 4.77, 'trade_success', 1000, 1000, 4775.0, 0, 'Order_l6QSycWF', 'Trade_pvkjxUOZ']\n",
      "receive deal\n",
      "741.9075000000103\n",
      "NOT ENOUGH MONEY FOR Order_l6QSycWF\n",
      "['JCSC_EXAMPLE', '2018-02-23 00:00:00', '2018-02-23 00:00:00', '300249', None, 1, 6.15, 6.15, 'trade_success', 1000, 1000, 6155.0, 0, 'Order_nMESg1jk', 'Trade_DYqu38Xs']\n",
      "receive deal\n",
      "741.9075000000103\n",
      "NOT ENOUGH MONEY FOR Order_nMESg1jk\n",
      "['JCSC_EXAMPLE', '2018-02-23 00:00:00', '2018-02-23 00:00:00', '300297', None, 1, 8.96, 8.96, 'trade_success', 1000, 1000, 8965.0, 0, 'Order_VpRG3DAS', 'Trade_DEmh4Szg']\n",
      "receive deal\n",
      "741.9075000000103\n",
      "NOT ENOUGH MONEY FOR Order_VpRG3DAS\n",
      "['JCSC_EXAMPLE', '2018-02-23 00:00:00', '2018-02-23 00:00:00', '300302', None, 1, 8.81, 8.806676737, 'trade_success', 1000, 1000, 8811.676737, 0, 'Order_QpAZdLOX', 'Trade_VJwbYPAS']\n",
      "receive deal\n",
      "741.9075000000103\n",
      "NOT ENOUGH MONEY FOR Order_QpAZdLOX\n",
      "['JCSC_EXAMPLE', '2018-02-23 00:00:00', '2018-02-23 00:00:00', '600198', None, 1, 7.36, 7.36, 'trade_success', 1000, 1000, 7365.0, 0, 'Order_fVK7S5Rn', 'Trade_yeMB8S6h']\n",
      "receive deal\n",
      "741.9075000000103\n",
      "NOT ENOUGH MONEY FOR Order_fVK7S5Rn\n",
      "['JCSC_EXAMPLE', '2018-02-23 00:00:00', '2018-02-23 00:00:00', '600536', None, 1, 12.23, 12.23, 'trade_success', 1000, 1000, 12235.0, 0, 'Order_NItxgiaf', 'Trade_F1siLYhT']\n",
      "receive deal\n",
      "741.9075000000103\n",
      "NOT ENOUGH MONEY FOR Order_NItxgiaf\n",
      "['JCSC_EXAMPLE', '2018-02-23 00:00:00', '2018-02-23 00:00:00', '600590', None, 1, 8.95, 8.95, 'trade_success', 1000, 1000, 8955.0, 0, 'Order_nE7S16IV', 'Trade_URz3ZJLM']\n",
      "receive deal\n",
      "741.9075000000103\n",
      "NOT ENOUGH MONEY FOR Order_nE7S16IV\n",
      "['JCSC_EXAMPLE', '2018-02-23 00:00:00', '2018-02-23 00:00:00', '600595', None, 1, 4.38, 4.38, 'trade_success', 1000, 1000, 4385.0, 0, 'Order_F3haEvSA', 'Trade_hkBtCaH2']\n",
      "receive deal\n",
      "741.9075000000103\n",
      "NOT ENOUGH MONEY FOR Order_F3haEvSA\n",
      "['JCSC_EXAMPLE', '2018-02-23 00:00:00', '2018-02-23 00:00:00', '600601', None, 1, 2.89, 2.89, 'trade_success', 1000, 1000, 2895.0, 0, 'Order_k8ORFiL9', 'Trade_xkeBYAKg']\n",
      "receive deal\n",
      "741.9075000000103\n",
      "NOT ENOUGH MONEY FOR Order_k8ORFiL9\n",
      "['JCSC_EXAMPLE', '2018-02-23 00:00:00', '2018-02-23 00:00:00', '600767', None, 1, 5.91, 5.91, 'trade_success', 1000, 1000, 5915.0, 0, 'Order_NDJdvmiG', 'Trade_t1bYZFre']\n",
      "receive deal\n",
      "741.9075000000103\n",
      "NOT ENOUGH MONEY FOR Order_NDJdvmiG\n",
      "['JCSC_EXAMPLE', '2018-02-23 00:00:00', '2018-02-23 00:00:00', '603138', None, 1, 36.33, 36.33, 'trade_success', 1000, 1000, 36339.0825, 0, 'Order_UL21Xa8g', 'Trade_Qb7HxL8V']\n",
      "receive deal\n",
      "741.9075000000103\n",
      "NOT ENOUGH MONEY FOR Order_UL21Xa8g\n",
      "['JCSC_EXAMPLE', '2018-02-26 00:00:00', '2018-02-26 00:00:00', '000021', None, 1, 8.5, 8.5, 'trade_success', 1000, 1000, 8505.0, 0, 'Order_BmwjMSZ4', 'Trade_LCWYw7l2']\n",
      "receive deal\n",
      "741.9075000000103\n",
      "NOT ENOUGH MONEY FOR Order_BmwjMSZ4\n",
      "['JCSC_EXAMPLE', '2018-02-26 00:00:00', '2018-02-26 00:00:00', '000070', None, 1, 8.9, 8.9, 'trade_success', 1000, 1000, 8905.0, 0, 'Order_8XG9hq43', 'Trade_knGDJs4E']\n",
      "receive deal\n",
      "741.9075000000103\n",
      "NOT ENOUGH MONEY FOR Order_8XG9hq43\n",
      "['JCSC_EXAMPLE', '2018-02-26 00:00:00', '2018-02-26 00:00:00', '002065', None, 1, 8.03, 8.03, 'trade_success', 1000, 1000, 8034.999999999999, 0, 'Order_3ugiLhsD', 'Trade_AyQfIFnG']\n",
      "receive deal\n",
      "741.9075000000103\n",
      "NOT ENOUGH MONEY FOR Order_3ugiLhsD\n",
      "['JCSC_EXAMPLE', '2018-02-26 00:00:00', '2018-02-26 00:00:00', '002315', None, 1, 18.96, 18.96, 'trade_success', 1000, 1000, 18965.0, 0, 'Order_xfI32KVm', 'Trade_MANTGfmB']\n",
      "receive deal\n",
      "741.9075000000103\n",
      "NOT ENOUGH MONEY FOR Order_xfI32KVm\n",
      "['JCSC_EXAMPLE', '2018-02-26 00:00:00', '2018-02-26 00:00:00', '002335', None, 1, 25.75, 25.749044201, 'trade_success', 1000, 1000, 25755.48146205025, 0, 'Order_2gUt1zyI', 'Trade_hdbvCxUe']\n",
      "receive deal\n",
      "741.9075000000103\n",
      "NOT ENOUGH MONEY FOR Order_2gUt1zyI\n",
      "['JCSC_EXAMPLE', '2018-02-26 00:00:00', '2018-02-26 00:00:00', '300020', None, 1, 10.14, 10.14, 'trade_success', 1000, 1000, 10145.0, 0, 'Order_523Lsaby', 'Trade_i1K96HdQ']\n",
      "receive deal\n",
      "741.9075000000103\n",
      "NOT ENOUGH MONEY FOR Order_523Lsaby\n",
      "['JCSC_EXAMPLE', '2018-02-26 00:00:00', '2018-02-26 00:00:00', '300052', None, 1, 13.38, 13.38, 'trade_success', 1000, 1000, 13385.0, 0, 'Order_kNH3AV8p', 'Trade_K95HwABX']\n",
      "receive deal\n",
      "741.9075000000103\n",
      "NOT ENOUGH MONEY FOR Order_kNH3AV8p\n",
      "['JCSC_EXAMPLE', '2018-02-26 00:00:00', '2018-02-26 00:00:00', '300085', None, 1, 14.08, 14.08, 'trade_success', 1000, 1000, 14085.0, 0, 'Order_RQ0pgSmO', 'Trade_YIsCLKa8']\n",
      "receive deal\n",
      "741.9075000000103\n",
      "NOT ENOUGH MONEY FOR Order_RQ0pgSmO\n",
      "['JCSC_EXAMPLE', '2018-02-26 00:00:00', '2018-02-26 00:00:00', '300235', None, 1, 10.14, 10.14, 'trade_success', 1000, 1000, 10145.0, 0, 'Order_NQChzxW8', 'Trade_XgqBkUP6']\n",
      "receive deal\n",
      "741.9075000000103\n",
      "NOT ENOUGH MONEY FOR Order_NQChzxW8\n",
      "['JCSC_EXAMPLE', '2018-02-26 00:00:00', '2018-02-26 00:00:00', '300245', None, 1, 12.54, 12.54, 'trade_success', 1000, 1000, 12545.0, 0, 'Order_2oxcR6Y3', 'Trade_lZ7Cpy9v']\n",
      "receive deal\n",
      "741.9075000000103\n",
      "NOT ENOUGH MONEY FOR Order_2oxcR6Y3\n",
      "['JCSC_EXAMPLE', '2018-02-26 00:00:00', '2018-02-26 00:00:00', '300274', None, 1, 16.46, 16.46, 'trade_success', 1000, 1000, 16465.0, 0, 'Order_GLCaBd8N', 'Trade_jtV4wGav']\n",
      "receive deal\n",
      "741.9075000000103\n",
      "NOT ENOUGH MONEY FOR Order_GLCaBd8N\n",
      "['JCSC_EXAMPLE', '2018-02-26 00:00:00', '2018-02-26 00:00:00', '300365', None, 1, 16.72, 16.7224376731, 'trade_success', 1000, 1000, 16727.4376731, 0, 'Order_tMLGxzpA', 'Trade_QiP6qjNp']\n",
      "receive deal\n",
      "741.9075000000103\n",
      "NOT ENOUGH MONEY FOR Order_tMLGxzpA\n",
      "['JCSC_EXAMPLE', '2018-02-26 00:00:00', '2018-02-26 00:00:00', '300366', None, 1, 9.82, 9.82, 'trade_success', 1000, 1000, 9825.0, 0, 'Order_RV5re1F0', 'Trade_Hu9x3FqP']\n",
      "receive deal\n",
      "741.9075000000103\n",
      "NOT ENOUGH MONEY FOR Order_RV5re1F0\n",
      "['JCSC_EXAMPLE', '2018-02-26 00:00:00', '2018-02-26 00:00:00', '300379', None, 1, 11.11, 11.11, 'trade_success', 1000, 1000, 11115.0, 0, 'Order_LKD31IB6', 'Trade_gNlL5GcF']\n",
      "receive deal\n",
      "741.9075000000103\n",
      "NOT ENOUGH MONEY FOR Order_LKD31IB6\n",
      "['JCSC_EXAMPLE', '2018-02-26 00:00:00', '2018-02-26 00:00:00', '300608', None, 1, 26.37, 26.37, 'trade_success', 1000, 1000, 26376.5925, 0, 'Order_gQeNIwlc', 'Trade_NvAUMmFS']\n",
      "receive deal\n",
      "741.9075000000103\n",
      "NOT ENOUGH MONEY FOR Order_gQeNIwlc\n",
      "['JCSC_EXAMPLE', '2018-02-26 00:00:00', '2018-02-26 00:00:00', '600105', None, 1, 5.42, 5.42, 'trade_success', 1000, 1000, 5425.0, 0, 'Order_ytlJ1kPC', 'Trade_NwV0hkFI']\n",
      "receive deal\n",
      "741.9075000000103\n",
      "NOT ENOUGH MONEY FOR Order_ytlJ1kPC\n",
      "['JCSC_EXAMPLE', '2018-02-26 00:00:00', '2018-02-26 00:00:00', '600602', None, 1, 6.73, 6.73, 'trade_success', 1000, 1000, 6735.0, 0, 'Order_gh8HNRfC', 'Trade_MZH7tVuR']\n",
      "receive deal\n",
      "741.9075000000103\n",
      "NOT ENOUGH MONEY FOR Order_gh8HNRfC\n",
      "['JCSC_EXAMPLE', '2018-02-26 00:00:00', '2018-02-26 00:00:00', '600756', None, 1, 14.56, 14.56, 'trade_success', 1000, 1000, 14565.0, 0, 'Order_5k7A1Xdh', 'Trade_QnP9H62O']\n",
      "receive deal\n",
      "741.9075000000103\n",
      "NOT ENOUGH MONEY FOR Order_5k7A1Xdh\n",
      "['JCSC_EXAMPLE', '2018-02-26 00:00:00', '2018-02-26 00:00:00', '600770', None, 1, 6.44, 6.44, 'trade_success', 1000, 1000, 6445.0, 0, 'Order_bxpGe63N', 'Trade_HDjzdyJq']\n",
      "receive deal\n",
      "741.9075000000103\n",
      "NOT ENOUGH MONEY FOR Order_bxpGe63N\n",
      "['JCSC_EXAMPLE', '2018-02-26 00:00:00', '2018-02-26 00:00:00', '600797', None, 1, 10.75, 10.75, 'trade_success', 1000, 1000, 10755.0, 0, 'Order_ioKPYsZa', 'Trade_C3tM5j9E']\n",
      "receive deal\n",
      "741.9075000000103\n",
      "NOT ENOUGH MONEY FOR Order_ioKPYsZa\n",
      "['JCSC_EXAMPLE', '2018-02-26 00:00:00', '2018-02-26 00:00:00', '601928', None, 1, 7.71, 7.71, 'trade_success', 1000, 1000, 7715.0, 0, 'Order_nF9BONgc', 'Trade_IGuSADo5']\n",
      "receive deal\n",
      "741.9075000000103\n",
      "NOT ENOUGH MONEY FOR Order_nF9BONgc\n",
      "['JCSC_EXAMPLE', '2018-02-26 00:00:00', '2018-02-26 00:00:00', '603003', None, 1, 10.71, 10.71, 'trade_success', 1000, 1000, 10715.0, 0, 'Order_CbzxtOL8', 'Trade_t7OHXhud']\n",
      "receive deal\n",
      "741.9075000000103\n",
      "NOT ENOUGH MONEY FOR Order_CbzxtOL8\n",
      "['JCSC_EXAMPLE', '2018-02-26 00:00:00', '2018-02-26 00:00:00', '603528', None, 1, 7.62, 7.622815534, 'trade_success', 1000, 1000, 7627.815534, 0, 'Order_KFEM4uQk', 'Trade_7K5f8cwe']\n",
      "receive deal\n",
      "741.9075000000103\n",
      "NOT ENOUGH MONEY FOR Order_KFEM4uQk\n",
      "['JCSC_EXAMPLE', '2018-02-26 00:00:00', '2018-02-26 00:00:00', '603881', None, 1, 35.38, 35.3771469087, 'trade_success', 1000, 1000, 35385.991195427174, 0, 'Order_XWikypgh', 'Trade_MwCPuRJN']\n",
      "receive deal\n",
      "741.9075000000103\n",
      "NOT ENOUGH MONEY FOR Order_XWikypgh\n",
      "['JCSC_EXAMPLE', '2018-02-27 00:00:00', '2018-02-27 00:00:00', '000066', None, 1, 6.6, 6.6, 'trade_success', 1000, 1000, 6605.0, 0, 'Order_Vywzb1hx', 'Trade_UeNAHEsa']\n",
      "receive deal\n",
      "741.9075000000103\n",
      "NOT ENOUGH MONEY FOR Order_Vywzb1hx\n",
      "['JCSC_EXAMPLE', '2018-02-27 00:00:00', '2018-02-27 00:00:00', '000665', None, 1, 9.48, 9.48, 'trade_success', 1000, 1000, 9485.0, 0, 'Order_IY17S8WU', 'Trade_BNLw6TWs']\n",
      "receive deal\n",
      "741.9075000000103\n",
      "NOT ENOUGH MONEY FOR Order_IY17S8WU\n",
      "['JCSC_EXAMPLE', '2018-02-27 00:00:00', '2018-02-27 00:00:00', '000971', None, 1, 5.82, 5.815, 'trade_success', 1000, 1000, 5820.0, 0, 'Order_67BRSsJg', 'Trade_yIKrd07k']\n",
      "receive deal\n",
      "741.9075000000103\n",
      "NOT ENOUGH MONEY FOR Order_67BRSsJg\n",
      "['JCSC_EXAMPLE', '2018-02-27 00:00:00', '2018-02-27 00:00:00', '002063', None, 1, 10.53, 10.53, 'trade_success', 1000, 1000, 10535.0, 0, 'Order_jhcDZTyE', 'Trade_L0FIUlOj']\n",
      "receive deal\n",
      "741.9075000000103\n",
      "NOT ENOUGH MONEY FOR Order_jhcDZTyE\n",
      "['JCSC_EXAMPLE', '2018-02-27 00:00:00', '2018-02-27 00:00:00', '002095', None, 1, 42.68, 42.68, 'trade_success', 1000, 1000, 42690.67, 0, 'Order_aNCJ1Vuj', 'Trade_x96UZw8C']\n",
      "receive deal\n",
      "741.9075000000103\n",
      "NOT ENOUGH MONEY FOR Order_aNCJ1Vuj\n",
      "['JCSC_EXAMPLE', '2018-02-27 00:00:00', '2018-02-27 00:00:00', '002195', None, 1, 5.86, 5.86, 'trade_success', 1000, 1000, 5865.0, 0, 'Order_czP8d7mq', 'Trade_XRFemn4l']\n",
      "receive deal\n",
      "741.9075000000103\n",
      "NOT ENOUGH MONEY FOR Order_czP8d7mq\n",
      "['JCSC_EXAMPLE', '2018-02-27 00:00:00', '2018-02-27 00:00:00', '002544', None, 1, 13.31, 13.31, 'trade_success', 1000, 1000, 13315.0, 0, 'Order_kBXKmpU1', 'Trade_1uXJW4ik']\n",
      "receive deal\n",
      "741.9075000000103\n",
      "NOT ENOUGH MONEY FOR Order_kBXKmpU1\n",
      "['JCSC_EXAMPLE', '2018-02-27 00:00:00', '2018-02-27 00:00:00', '002657', None, 1, 19.11, 19.11, 'trade_success', 1000, 1000, 19115.0, 0, 'Order_jfU6rO4h', 'Trade_zbHOCTtX']\n",
      "receive deal\n",
      "741.9075000000103\n",
      "NOT ENOUGH MONEY FOR Order_jfU6rO4h\n",
      "['JCSC_EXAMPLE', '2018-02-27 00:00:00', '2018-02-27 00:00:00', '300017', None, 1, 12.3, 12.3, 'trade_success', 1000, 1000, 12305.0, 0, 'Order_XmSpkN9u', 'Trade_1c4ZxwR3']\n",
      "receive deal\n",
      "741.9075000000103\n",
      "NOT ENOUGH MONEY FOR Order_XmSpkN9u\n",
      "['JCSC_EXAMPLE', '2018-02-27 00:00:00', '2018-02-27 00:00:00', '300051', None, 1, 9.71, 9.71, 'trade_success', 1000, 1000, 9715.0, 0, 'Order_2sIav89X', 'Trade_st2MazQ1']\n",
      "receive deal\n",
      "741.9075000000103\n",
      "NOT ENOUGH MONEY FOR Order_2sIav89X\n",
      "['JCSC_EXAMPLE', '2018-02-27 00:00:00', '2018-02-27 00:00:00', '300730', None, 1, 33.25, 33.25, 'trade_success', 1000, 1000, 33258.3125, 0, 'Order_gFqbm8IA', 'Trade_MRP7hZs4']\n",
      "receive deal\n",
      "741.9075000000103\n",
      "NOT ENOUGH MONEY FOR Order_gFqbm8IA\n",
      "['JCSC_EXAMPLE', '2018-02-27 00:00:00', '2018-02-27 00:00:00', '600037', None, 1, 12.23, 12.23, 'trade_success', 1000, 1000, 12235.0, 0, 'Order_KxFI1SUT', 'Trade_dOlbHwKp']\n",
      "receive deal\n",
      "741.9075000000103\n",
      "NOT ENOUGH MONEY FOR Order_KxFI1SUT\n",
      "['JCSC_EXAMPLE', '2018-02-27 00:00:00', '2018-02-27 00:00:00', '600225', None, 1, 4.09, 4.09, 'trade_success', 1000, 1000, 4095.0, 0, 'Order_0Hq7doyM', 'Trade_uSpsc56g']\n",
      "receive deal\n",
      "741.9075000000103\n",
      "NOT ENOUGH MONEY FOR Order_0Hq7doyM\n",
      "['JCSC_EXAMPLE', '2018-02-27 00:00:00', '2018-02-27 00:00:00', '600589', None, 1, 5.58, 5.58, 'trade_success', 1000, 1000, 5585.0, 0, 'Order_5bMEPqgA', 'Trade_7e6JH9Qm']\n",
      "receive deal\n",
      "741.9075000000103\n",
      "NOT ENOUGH MONEY FOR Order_5bMEPqgA\n",
      "['JCSC_EXAMPLE', '2018-02-27 00:00:00', '2018-02-27 00:00:00', '600633', None, 1, 13.68, 13.68, 'trade_success', 1000, 1000, 13685.0, 0, 'Order_2KXyka4O', 'Trade_6ZbBYWgu']\n",
      "receive deal\n",
      "741.9075000000103\n",
      "NOT ENOUGH MONEY FOR Order_2KXyka4O\n",
      "['JCSC_EXAMPLE', '2018-02-28 00:00:00', '2018-02-28 00:00:00', '000836', None, 1, 5.32, 5.32, 'trade_success', 1000, 1000, 5325.0, 0, 'Order_kzdGn8uQ', 'Trade_0cutYwyx']\n",
      "receive deal\n",
      "741.9075000000103\n",
      "NOT ENOUGH MONEY FOR Order_kzdGn8uQ\n",
      "['JCSC_EXAMPLE', '2018-02-28 00:00:00', '2018-02-28 00:00:00', '600996', None, 1, 9.36, 9.36, 'trade_success', 1000, 1000, 9365.0, 0, 'Order_dBaJvEKb', 'Trade_6PmOWSTw']\n",
      "receive deal\n",
      "741.9075000000103\n",
      "NOT ENOUGH MONEY FOR Order_dBaJvEKb\n",
      "['JCSC_EXAMPLE', '2018-03-02 00:00:00', '2018-03-02 00:00:00', '601360', None, -1, 52.51, 52.510000000000005, 'trade_success', 1000.0, 1000.0, 52601.89250000001, 0, 'Order_vnsuhYHg', 'Trade_6KoeGBCr']\n",
      "receive deal\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['JCSC_EXAMPLE', '2018-03-07 00:00:00', '2018-03-07 00:00:00', '300113', None, -1, 22.67, 22.67, 'trade_success', 1000.0, 1000.0, 22709.6725, 0, 'Order_cDrkeblm', 'Trade_IxeuwnMH']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-03-09 00:00:00', '2018-03-07 00:00:00', '000948', None, 1, 0.0, 9.9, 'trade_price_limit', 1000, 0, 5, 0, 'Order_f512YgQF', 'Trade_8OZJwhQI']\n",
      "['JCSC_EXAMPLE', '2018-03-09 00:00:00', '2018-03-09 00:00:00', '300212', None, 1, 33.08, 33.08, 'trade_success', 1000, 1000, 33088.27, 0, 'Order_QZSuPY2A', 'Trade_j38HQRl0']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-03-12 00:00:00', '2018-03-12 00:00:00', '300113', None, 1, 24.08, 24.08, 'trade_success', 1000, 1000, 24086.02, 0, 'Order_OZ87YLkF', 'Trade_5ZVaqfRy']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-03-14 00:00:00', '2018-03-14 00:00:00', '300113', None, -1, 23.7, 23.695, 'trade_success', 1000.0, 1000.0, 23736.46625, 0, 'Order_MOFWBefc', 'Trade_DuLSBUKA']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-03-14 00:00:00', '2018-03-14 00:00:00', '300212', None, -1, 32.31, 32.31, 'trade_success', 1000.0, 1000.0, 32366.542500000003, 0, 'Order_tHh7RwiP', 'Trade_Cgpcd0JT']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-03-16 00:00:00', '2018-03-16 00:00:00', '002279', None, -1, 12.42, 12.42, 'trade_success', 1000.0, 1000.0, 12443.63, 0, 'Order_lvRjTUGc', 'Trade_gYvo6MSD']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-03-16 00:00:00', '2018-03-16 00:00:00', '002456', None, -1, 21.31, 21.310000000000002, 'trade_success', 1000.0, 1000.0, 21347.292500000003, 0, 'Order_bI0ci74C', 'Trade_GWkpSPNo']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-03-16 00:00:00', '2018-03-16 00:00:00', '300044', None, -1, 9.64, 9.6356469279, 'trade_success', 1000.0, 1000.0, 9655.10039829185, 0, 'Order_VWoT4DXj', 'Trade_eC9qB5nU']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-03-16 00:00:00', '2018-03-16 00:00:00', '300287', None, -1, 9.43, 9.425, 'trade_success', 1000.0, 1000.0, 9444.1375, 0, 'Order_2GybvxAO', 'Trade_TvPJ2Mab']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-03-16 00:00:00', '2018-03-16 00:00:00', '300431', None, -1, 27.55, 27.555, 'trade_success', 1000.0, 1000.0, 27603.22125, 0, 'Order_p28GeiTK', 'Trade_dmb1TwEv']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-03-16 00:00:00', '2018-03-16 00:00:00', '600804', None, 1, 14.87, 14.87, 'trade_success', 1000, 1000, 14875.0, 0, 'Order_92Ji4hIu', 'Trade_KXwWES09']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-03-19 00:00:00', '2018-03-19 00:00:00', '300287', None, 1, 9.89, 9.89, 'trade_success', 1000, 1000, 9895.0, 0, 'Order_uknEJK6L', 'Trade_60MuJFhL']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-03-20 00:00:00', '2018-03-20 00:00:00', '002837', None, -1, 19.95, 19.950000000000003, 'trade_success', 1000.0, 1000.0, 19984.925000000003, 0, 'Order_UQKczxw9', 'Trade_esHVhkX6']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-03-20 00:00:00', '2018-03-20 00:00:00', '300383', None, 1, 15.94, 15.9383300468, 'trade_success', 1000, 1000, 15943.330046800002, 0, 'Order_INSlznaC', 'Trade_5EB8Nmgd']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-03-21 00:00:00', '2018-03-21 00:00:00', '002417', None, 1, 11.55, 11.55, 'trade_success', 1000, 1000, 11555.0, 0, 'Order_WxTMfcjE', 'Trade_GwUEOylT']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-03-21 00:00:00', '2018-03-21 00:00:00', '002837', None, 1, 21.96, 21.96, 'trade_success', 1000, 1000, 21965.49, 0, 'Order_fsWOZ3TD', 'Trade_Hxp5n6XZ']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-03-21 00:00:00', '2018-03-21 00:00:00', '300287', None, -1, 9.57, 9.57, 'trade_success', 1000.0, 1000.0, 9589.355, 0, 'Order_zlkqUcmA', 'Trade_OngFv6Ya']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-03-22 00:00:00', '2018-03-22 00:00:00', '000100', None, -1, 3.67, 3.67, 'trade_success', 1000.0, 1000.0, 3680.505, 0, 'Order_QmYxMA9g', 'Trade_UzqYEtJT']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-03-22 00:00:00', '2018-03-22 00:00:00', '603138', None, 1, 43.07, 43.07, 'trade_success', 1000, 1000, 43080.7675, 0, 'Order_tsRz9Z0U', 'Trade_h3TQzbsm']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-03-23 00:00:00', '2018-03-23 00:00:00', '000977', None, -1, 20.49, 20.48959680845, 'trade_success', 1000.0, 1000.0, 20525.453602864785, 0, 'Order_x7HlrIKC', 'Trade_CILgMXBq']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-03-23 00:00:00', '2018-03-23 00:00:00', '603138', None, -1, 40.12, 40.125, 'trade_success', 1000.0, 1000.0, 40195.21875, 0, 'Order_07R3gO9Z', 'Trade_qHohjRVJ']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-03-26 00:00:00', '2018-03-26 00:00:00', '000977', None, 1, 22.38, 22.3813281581, 'trade_success', 1000, 1000, 22386.923490139525, 0, 'Order_1pbogE8t', 'Trade_VWJurH01']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-03-26 00:00:00', '2018-03-26 00:00:00', '300365', None, 1, 20.98, 20.977700831, 'trade_success', 1000, 1000, 20982.94525620775, 0, 'Order_pRMmFIjz', 'Trade_bgrT2SX0']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-03-26 00:00:00', '2018-03-26 00:00:00', '300738', None, 1, 77.77, 77.77, 'trade_success', 1000, 1000, 77789.4425, 0, 'Order_a1QzE5qU', 'Trade_c9PLzEWr']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-03-26 00:00:00', '2018-03-26 00:00:00', '600756', None, 1, 16.63, 16.63, 'trade_success', 1000, 1000, 16635.0, 0, 'Order_PxHzQ4ab', 'Trade_0ue5NOZ2']\n",
      "receive deal\n",
      "10529.005000000034\n",
      "NOT ENOUGH MONEY FOR Order_PxHzQ4ab\n",
      "['JCSC_EXAMPLE', '2018-03-27 00:00:00', '2018-03-27 00:00:00', '000066', None, 1, 7.88, 7.88, 'trade_success', 1000, 1000, 7885.0, 0, 'Order_1GPcBned', 'Trade_7HbmTwcJ']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-03-27 00:00:00', '2018-03-27 00:00:00', '002642', None, 1, 12.65, 12.65, 'trade_success', 1000, 1000, 12655.0, 0, 'Order_ZuCKX0eQ', 'Trade_FCRnyMJ7']\n",
      "receive deal\n",
      "2635.215000000034\n",
      "NOT ENOUGH MONEY FOR Order_ZuCKX0eQ\n",
      "['JCSC_EXAMPLE', '2018-03-27 00:00:00', '2018-03-27 00:00:00', '300036', None, 1, 17.61, 17.6093409331, 'trade_success', 1000, 1000, 17614.3409331, 0, 'Order_wD5x4Vbi', 'Trade_dvnCBMJ0']\n",
      "receive deal\n",
      "2635.215000000034\n",
      "NOT ENOUGH MONEY FOR Order_wD5x4Vbi\n",
      "['JCSC_EXAMPLE', '2018-03-27 00:00:00', '2018-03-27 00:00:00', '300188', None, 1, 29.44, 29.44, 'trade_success', 1000, 1000, 29447.36, 0, 'Order_r6oYAsRj', 'Trade_DnrefL45']\n",
      "receive deal\n",
      "2635.215000000034\n",
      "NOT ENOUGH MONEY FOR Order_r6oYAsRj\n",
      "['JCSC_EXAMPLE', '2018-03-27 00:00:00', '2018-03-27 00:00:00', '300229', None, 1, 15.0, 15.0, 'trade_success', 1000, 1000, 15005.0, 0, 'Order_2je98KiW', 'Trade_juK5nrtf']\n",
      "receive deal\n",
      "2635.215000000034\n",
      "NOT ENOUGH MONEY FOR Order_2je98KiW\n",
      "['JCSC_EXAMPLE', '2018-03-27 00:00:00', '2018-03-27 00:00:00', '300249', None, 1, 7.65, 7.65, 'trade_success', 1000, 1000, 7655.0, 0, 'Order_MXUo8bqW', 'Trade_HVYvwIPa']\n",
      "receive deal\n",
      "2635.215000000034\n",
      "NOT ENOUGH MONEY FOR Order_MXUo8bqW\n",
      "['JCSC_EXAMPLE', '2018-03-27 00:00:00', '2018-03-27 00:00:00', '300274', None, 1, 18.46, 18.46, 'trade_success', 1000, 1000, 18465.0, 0, 'Order_ySUzjuOo', 'Trade_pIDkfyJR']\n",
      "receive deal\n",
      "2635.215000000034\n",
      "NOT ENOUGH MONEY FOR Order_ySUzjuOo\n",
      "['JCSC_EXAMPLE', '2018-03-27 00:00:00', '2018-03-27 00:00:00', '300367', None, 1, 18.23, 18.23, 'trade_success', 1000, 1000, 18235.0, 0, 'Order_nhfFyw86', 'Trade_T8VCsjg3']\n",
      "receive deal\n",
      "2635.215000000034\n",
      "NOT ENOUGH MONEY FOR Order_nhfFyw86\n",
      "['JCSC_EXAMPLE', '2018-03-27 00:00:00', '2018-03-27 00:00:00', '603019', None, 1, 53.81, 53.8072751524, 'trade_success', 1000, 1000, 53820.7269711881, 0, 'Order_OjrUnQ39', 'Trade_DykN3E7Y']\n",
      "receive deal\n",
      "2635.215000000034\n",
      "NOT ENOUGH MONEY FOR Order_OjrUnQ39\n",
      "['JCSC_EXAMPLE', '2018-03-27 00:00:00', '2018-03-27 00:00:00', '603138', None, 1, 42.38, 42.38, 'trade_success', 1000, 1000, 42390.595, 0, 'Order_1FTxgES0', 'Trade_P6Zz9gJV']\n",
      "receive deal\n",
      "2635.215000000034\n",
      "NOT ENOUGH MONEY FOR Order_1FTxgES0\n",
      "['JCSC_EXAMPLE', '2018-03-28 00:00:00', '2018-03-28 00:00:00', '002368', None, 1, 26.21, 26.21, 'trade_success', 1000, 1000, 26216.5525, 0, 'Order_dDQyw3nM', 'Trade_uc2jSbIM']\n",
      "receive deal\n",
      "2635.215000000034\n",
      "NOT ENOUGH MONEY FOR Order_dDQyw3nM\n",
      "['JCSC_EXAMPLE', '2018-03-28 00:00:00', '2018-03-28 00:00:00', '002439', None, 1, 25.04, 25.0363200685, 'trade_success', 1000, 1000, 25042.579148517125, 0, 'Order_fgm2d8Nn', 'Trade_BRSAv4yO']\n",
      "receive deal\n",
      "2635.215000000034\n",
      "NOT ENOUGH MONEY FOR Order_fgm2d8Nn\n",
      "['JCSC_EXAMPLE', '2018-03-28 00:00:00', '2018-03-28 00:00:00', '300078', None, 1, 10.3, 10.3, 'trade_success', 1000, 1000, 10305.0, 0, 'Order_DcKoMRSx', 'Trade_qQa5dGWA']\n",
      "receive deal\n",
      "2635.215000000034\n",
      "NOT ENOUGH MONEY FOR Order_DcKoMRSx\n",
      "['JCSC_EXAMPLE', '2018-03-28 00:00:00', '2018-03-28 00:00:00', '300311', None, 1, 13.92, 13.92, 'trade_success', 1000, 1000, 13925.0, 0, 'Order_7NsXHZcx', 'Trade_L2rnlQq0']\n",
      "receive deal\n",
      "2635.215000000034\n",
      "NOT ENOUGH MONEY FOR Order_7NsXHZcx\n",
      "['JCSC_EXAMPLE', '2018-03-29 00:00:00', '2018-03-29 00:00:00', '002315', None, 1, 20.86, 20.86, 'trade_success', 1000, 1000, 20865.215, 0, 'Order_tHbQUT07', 'Trade_DLpVuZfa']\n",
      "receive deal\n",
      "2635.215000000034\n",
      "NOT ENOUGH MONEY FOR Order_tHbQUT07\n",
      "['JCSC_EXAMPLE', '2018-03-29 00:00:00', '2018-03-29 00:00:00', '300235', None, 1, 11.88, 11.88, 'trade_success', 1000, 1000, 11885.0, 0, 'Order_AM5vw6mL', 'Trade_TNZuAQf9']\n",
      "receive deal\n",
      "2635.215000000034\n",
      "NOT ENOUGH MONEY FOR Order_AM5vw6mL\n",
      "['JCSC_EXAMPLE', '2018-03-29 00:00:00', '2018-03-29 00:00:00', '300297', None, 1, 9.99, 9.99, 'trade_success', 1000, 1000, 9995.0, 0, 'Order_B3XDE0m5', 'Trade_sTCMamnY']\n",
      "receive deal\n",
      "2635.215000000034\n",
      "NOT ENOUGH MONEY FOR Order_B3XDE0m5\n",
      "['JCSC_EXAMPLE', '2018-03-29 00:00:00', '2018-03-29 00:00:00', '600718', None, 1, 14.19, 14.19, 'trade_success', 1000, 1000, 14195.0, 0, 'Order_W1Y4lP6a', 'Trade_bOu9K2Lh']\n",
      "receive deal\n",
      "2635.215000000034\n",
      "NOT ENOUGH MONEY FOR Order_W1Y4lP6a\n",
      "['JCSC_EXAMPLE', '2018-03-29 00:00:00', '2018-03-29 00:00:00', '600850', None, 1, 18.08, 18.08, 'trade_success', 1000, 1000, 18085.0, 0, 'Order_p2FPYAZz', 'Trade_W0mdaOo3']\n",
      "receive deal\n",
      "2635.215000000034\n",
      "NOT ENOUGH MONEY FOR Order_p2FPYAZz\n",
      "['JCSC_EXAMPLE', '2018-03-30 00:00:00', '2018-03-30 00:00:00', '000070', None, 1, 9.5, 9.5, 'trade_success', 1000, 1000, 9505.0, 0, 'Order_wNqs05Qa', 'Trade_w56QRkMY']\n",
      "receive deal\n",
      "2635.215000000034\n",
      "NOT ENOUGH MONEY FOR Order_wNqs05Qa\n",
      "['JCSC_EXAMPLE', '2018-03-30 00:00:00', '2018-03-30 00:00:00', '000938', None, 1, 72.85, 72.85, 'trade_success', 1000, 1000, 72868.2125, 0, 'Order_XfIUgkxs', 'Trade_6XJOt3wV']\n",
      "receive deal\n",
      "2635.215000000034\n",
      "NOT ENOUGH MONEY FOR Order_XfIUgkxs\n",
      "['JCSC_EXAMPLE', '2018-03-30 00:00:00', '2018-03-30 00:00:00', '002063', None, 1, 11.37, 11.37, 'trade_success', 1000, 1000, 11375.0, 0, 'Order_tC8MPAXD', 'Trade_jikQ2COM']\n",
      "receive deal\n",
      "2635.215000000034\n",
      "NOT ENOUGH MONEY FOR Order_tC8MPAXD\n",
      "['JCSC_EXAMPLE', '2018-03-30 00:00:00', '2018-03-30 00:00:00', '002093', None, 1, 9.17, 9.17, 'trade_success', 1000, 1000, 9175.0, 0, 'Order_tkFxKg0P', 'Trade_wPzlCLix']\n",
      "receive deal\n",
      "2635.215000000034\n",
      "NOT ENOUGH MONEY FOR Order_tkFxKg0P\n",
      "['JCSC_EXAMPLE', '2018-03-30 00:00:00', '2018-03-30 00:00:00', '002281', None, 1, 28.73, 28.73, 'trade_success', 1000, 1000, 28737.1825, 0, 'Order_QGZVzdlp', 'Trade_W7HcnOaB']\n",
      "receive deal\n",
      "2635.215000000034\n",
      "NOT ENOUGH MONEY FOR Order_QGZVzdlp\n",
      "['JCSC_EXAMPLE', '2018-03-30 00:00:00', '2018-03-30 00:00:00', '002396', None, 1, 24.43, 24.43, 'trade_success', 1000, 1000, 24436.1075, 0, 'Order_Lf4Pi1Nr', 'Trade_W4c0vgyX']\n",
      "receive deal\n",
      "2635.215000000034\n",
      "NOT ENOUGH MONEY FOR Order_Lf4Pi1Nr\n",
      "['JCSC_EXAMPLE', '2018-03-30 00:00:00', '2018-03-30 00:00:00', '002657', None, 1, 20.61, 20.61, 'trade_success', 1000, 1000, 20615.1525, 0, 'Order_tEL3GUlk', 'Trade_Qf47mOuK']\n",
      "receive deal\n",
      "2635.215000000034\n",
      "NOT ENOUGH MONEY FOR Order_tEL3GUlk\n",
      "['JCSC_EXAMPLE', '2018-03-30 00:00:00', '2018-03-30 00:00:00', '300017', None, 1, 14.95, 14.95, 'trade_success', 1000, 1000, 14955.0, 0, 'Order_7GTFvLCl', 'Trade_EYt3ZUpN']\n",
      "receive deal\n",
      "2635.215000000034\n",
      "NOT ENOUGH MONEY FOR Order_7GTFvLCl\n",
      "['JCSC_EXAMPLE', '2018-03-30 00:00:00', '2018-03-30 00:00:00', '300020', None, 1, 11.95, 11.95, 'trade_success', 1000, 1000, 11955.0, 0, 'Order_yOS3eXU4', 'Trade_VnBeFri5']\n",
      "receive deal\n",
      "2635.215000000034\n",
      "NOT ENOUGH MONEY FOR Order_yOS3eXU4\n",
      "['JCSC_EXAMPLE', '2018-03-30 00:00:00', '2018-03-30 00:00:00', '300271', None, 1, 20.49, 20.49, 'trade_success', 1000, 1000, 20495.1225, 0, 'Order_iqORn0oc', 'Trade_8xoS74rE']\n",
      "receive deal\n",
      "2635.215000000034\n",
      "NOT ENOUGH MONEY FOR Order_iqORn0oc\n",
      "['JCSC_EXAMPLE', '2018-03-30 00:00:00', '2018-03-30 00:00:00', '300366', None, 1, 12.19, 12.19, 'trade_success', 1000, 1000, 12195.0, 0, 'Order_DcZbAISl', 'Trade_OouLSVzr']\n",
      "receive deal\n",
      "2635.215000000034\n",
      "NOT ENOUGH MONEY FOR Order_DcZbAISl\n",
      "['JCSC_EXAMPLE', '2018-03-30 00:00:00', '2018-03-30 00:00:00', '300369', None, 1, 14.09, 14.09, 'trade_success', 1000, 1000, 14095.0, 0, 'Order_DELcxOVp', 'Trade_sHdEAKmz']\n",
      "receive deal\n",
      "2635.215000000034\n",
      "NOT ENOUGH MONEY FOR Order_DELcxOVp\n",
      "['JCSC_EXAMPLE', '2018-03-30 00:00:00', '2018-03-30 00:00:00', '600105', None, 1, 5.62, 5.62, 'trade_success', 1000, 1000, 5625.0, 0, 'Order_fzFJIc6T', 'Trade_q1UzI7Cu']\n",
      "receive deal\n",
      "2635.215000000034\n",
      "NOT ENOUGH MONEY FOR Order_fzFJIc6T\n",
      "['JCSC_EXAMPLE', '2018-03-30 00:00:00', '2018-03-30 00:00:00', '600198', None, 1, 8.22, 8.22, 'trade_success', 1000, 1000, 8225.0, 0, 'Order_KgyRcaWI', 'Trade_EBUPdQnz']\n",
      "receive deal\n",
      "2635.215000000034\n",
      "NOT ENOUGH MONEY FOR Order_KgyRcaWI\n",
      "['JCSC_EXAMPLE', '2018-03-30 00:00:00', '2018-03-30 00:00:00', '600602', None, 1, 7.88, 7.88, 'trade_success', 1000, 1000, 7885.0, 0, 'Order_ZBDmziH2', 'Trade_TLoSnciQ']\n",
      "receive deal\n",
      "2635.215000000034\n",
      "NOT ENOUGH MONEY FOR Order_ZBDmziH2\n",
      "['JCSC_EXAMPLE', '2018-03-30 00:00:00', '2018-03-30 00:00:00', '600797', None, 1, 12.48, 12.48, 'trade_success', 1000, 1000, 12485.0, 0, 'Order_TZPyfjxz', 'Trade_SY2CJna9']\n",
      "receive deal\n",
      "2635.215000000034\n",
      "NOT ENOUGH MONEY FOR Order_TZPyfjxz\n",
      "['JCSC_EXAMPLE', '2018-03-30 00:00:00', '2018-03-30 00:00:00', '600845', None, 1, 27.54, 27.5397989747, 'trade_success', 1000, 1000, 27546.683924443674, 0, 'Order_GLfJc2Yx', 'Trade_zK3r0kdg']\n",
      "receive deal\n",
      "2635.215000000034\n",
      "NOT ENOUGH MONEY FOR Order_GLfJc2Yx\n",
      "['JCSC_EXAMPLE', '2018-03-30 00:00:00', '2018-03-30 00:00:00', '603528', None, 1, 9.1, 9.095631068, 'trade_success', 1000, 1000, 9100.631067999999, 0, 'Order_nkAGfSHO', 'Trade_DqbAyIlz']\n",
      "receive deal\n",
      "2635.215000000034\n",
      "NOT ENOUGH MONEY FOR Order_nkAGfSHO\n",
      "['JCSC_EXAMPLE', '2018-04-02 00:00:00', '2018-04-02 00:00:00', '000021', None, 1, 8.94, 8.94, 'trade_success', 1000, 1000, 8945.0, 0, 'Order_S0FpVE6i', 'Trade_jZEpiKlb']\n",
      "receive deal\n",
      "2635.215000000034\n",
      "NOT ENOUGH MONEY FOR Order_S0FpVE6i\n",
      "['JCSC_EXAMPLE', '2018-04-02 00:00:00', '2018-04-02 00:00:00', '002065', None, 1, 8.57, 8.57, 'trade_success', 1000, 1000, 8575.0, 0, 'Order_MwRY3iH1', 'Trade_fibh5K6o']\n",
      "receive deal\n",
      "2635.215000000034\n",
      "NOT ENOUGH MONEY FOR Order_MwRY3iH1\n",
      "['JCSC_EXAMPLE', '2018-04-02 00:00:00', '2018-04-02 00:00:00', '002279', None, 1, 13.53, 13.53, 'trade_success', 1000, 1000, 13535.0, 0, 'Order_ER2YqWkI', 'Trade_pjTIUzsF']\n",
      "receive deal\n",
      "2635.215000000034\n",
      "NOT ENOUGH MONEY FOR Order_ER2YqWkI\n",
      "['JCSC_EXAMPLE', '2018-04-02 00:00:00', '2018-04-02 00:00:00', '002335', None, 1, 27.48, 27.4810426898, 'trade_success', 1000, 1000, 27487.91295047245, 0, 'Order_9KAtzkBQ', 'Trade_IknhcQs5']\n",
      "receive deal\n",
      "2635.215000000034\n",
      "NOT ENOUGH MONEY FOR Order_9KAtzkBQ\n",
      "['JCSC_EXAMPLE', '2018-04-02 00:00:00', '2018-04-02 00:00:00', '300044', None, 1, 10.26, 10.2617700463, 'trade_success', 1000, 1000, 10266.7700463, 0, 'Order_KmOTJobH', 'Trade_xV6RXoGW']\n",
      "receive deal\n",
      "2635.215000000034\n",
      "NOT ENOUGH MONEY FOR Order_KmOTJobH\n",
      "['JCSC_EXAMPLE', '2018-04-02 00:00:00', '2018-04-02 00:00:00', '300052', None, 1, 14.54, 14.54, 'trade_success', 1000, 1000, 14545.0, 0, 'Order_8j5VzwFK', 'Trade_m5JEv9fF']\n",
      "receive deal\n",
      "2635.215000000034\n",
      "NOT ENOUGH MONEY FOR Order_8j5VzwFK\n",
      "['JCSC_EXAMPLE', '2018-04-02 00:00:00', '2018-04-02 00:00:00', '300212', None, 1, 34.11, 34.11, 'trade_success', 1000, 1000, 34118.5275, 0, 'Order_elFhIAdt', 'Trade_Raw9P3iE']\n",
      "receive deal\n",
      "2635.215000000034\n",
      "NOT ENOUGH MONEY FOR Order_elFhIAdt\n",
      "['JCSC_EXAMPLE', '2018-04-02 00:00:00', '2018-04-02 00:00:00', '300245', None, 1, 13.83, 13.83, 'trade_success', 1000, 1000, 13835.0, 0, 'Order_qvxj7OaQ', 'Trade_R1HoSk2W']\n",
      "receive deal\n",
      "2635.215000000034\n",
      "NOT ENOUGH MONEY FOR Order_qvxj7OaQ\n",
      "['JCSC_EXAMPLE', '2018-04-02 00:00:00', '2018-04-02 00:00:00', '600100', None, 1, 10.97, 10.97, 'trade_success', 1000, 1000, 10975.0, 0, 'Order_pZ4PClqO', 'Trade_UgKR2oF3']\n",
      "receive deal\n",
      "2635.215000000034\n",
      "NOT ENOUGH MONEY FOR Order_pZ4PClqO\n",
      "['JCSC_EXAMPLE', '2018-04-02 00:00:00', '2018-04-02 00:00:00', '600225', None, 1, 4.21, 4.21, 'trade_success', 1000, 1000, 4215.0, 0, 'Order_DIMOjqz3', 'Trade_ymkoPlH6']\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "receive deal\n",
      "2635.215000000034\n",
      "NOT ENOUGH MONEY FOR Order_DIMOjqz3\n",
      "['JCSC_EXAMPLE', '2018-04-02 00:00:00', '2018-04-02 00:00:00', '600410', None, 1, 12.22, 12.22, 'trade_success', 1000, 1000, 12225.0, 0, 'Order_7ksGX1bp', 'Trade_4uGitzmZ']\n",
      "receive deal\n",
      "2635.215000000034\n",
      "NOT ENOUGH MONEY FOR Order_7ksGX1bp\n",
      "['JCSC_EXAMPLE', '2018-04-02 00:00:00', '2018-04-02 00:00:00', '600601', None, 1, 3.22, 3.22, 'trade_success', 1000, 1000, 3225.0, 0, 'Order_1pon7FMg', 'Trade_lrG1WN7U']\n",
      "receive deal\n",
      "2635.215000000034\n",
      "NOT ENOUGH MONEY FOR Order_1pon7FMg\n",
      "['JCSC_EXAMPLE', '2018-04-03 00:00:00', '2018-04-03 00:00:00', '002195', None, 1, 5.85, 5.85, 'trade_success', 1000, 1000, 5855.0, 0, 'Order_fCDH3WKc', 'Trade_tNALEa2S']\n",
      "receive deal\n",
      "2635.215000000034\n",
      "NOT ENOUGH MONEY FOR Order_fCDH3WKc\n",
      "['JCSC_EXAMPLE', '2018-04-03 00:00:00', '2018-04-03 00:00:00', '002197', None, 1, 10.36, 10.36, 'trade_success', 1000, 1000, 10365.0, 0, 'Order_zgF9w8RD', 'Trade_twVOUfD1']\n",
      "receive deal\n",
      "2635.215000000034\n",
      "NOT ENOUGH MONEY FOR Order_zgF9w8RD\n",
      "['JCSC_EXAMPLE', '2018-04-03 00:00:00', '2018-04-03 00:00:00', '002268', None, 1, 30.3, 30.3, 'trade_success', 1000, 1000, 30307.575, 0, 'Order_fSGOU6R7', 'Trade_ItuYGWqg']\n",
      "receive deal\n",
      "2635.215000000034\n",
      "NOT ENOUGH MONEY FOR Order_fSGOU6R7\n",
      "['JCSC_EXAMPLE', '2018-04-03 00:00:00', '2018-04-03 00:00:00', '300113', None, 1, 22.45, 22.45, 'trade_success', 1000, 1000, 22455.6125, 0, 'Order_piH9hPGx', 'Trade_nD7MTuRU']\n",
      "receive deal\n",
      "2635.215000000034\n",
      "NOT ENOUGH MONEY FOR Order_piH9hPGx\n",
      "['JCSC_EXAMPLE', '2018-04-03 00:00:00', '2018-04-03 00:00:00', '600770', None, 1, 7.15, 7.15, 'trade_success', 1000, 1000, 7155.0, 0, 'Order_gf08OQFE', 'Trade_OkVicnLW']\n",
      "receive deal\n",
      "2635.215000000034\n",
      "NOT ENOUGH MONEY FOR Order_gf08OQFE\n",
      "['JCSC_EXAMPLE', '2018-04-04 00:00:00', '2018-04-04 00:00:00', '002837', None, -1, 22.04, 22.035, 'trade_success', 1000.0, 1000.0, 22073.561250000002, 0, 'Order_AHKmvINs', 'Trade_CrP2N6Di']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-04-04 00:00:00', '2018-04-04 00:00:00', '300085', None, 1, 16.8, 16.8, 'trade_success', 1000, 1000, 16805.0, 0, 'Order_ynFVwGEp', 'Trade_d3MhbXav']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-04-04 00:00:00', '2018-04-04 00:00:00', '300738', None, -1, 75.7, 75.69999999999999, 'trade_success', 1000.0, 1000.0, 75832.47499999999, 0, 'Order_0AJVy9M5', 'Trade_u9bhyRi6']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-04-09 00:00:00', '2018-04-09 00:00:00', '300738', None, 1, 80.15, 80.15, 'trade_success', 1000, 1000, 80170.0375, 0, 'Order_UKCRsI5t', 'Trade_qFTDN0mL']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-04-10 00:00:00', '2018-04-10 00:00:00', '000063', None, 1, 30.7, 30.7, 'trade_success', 1000, 1000, 30707.675, 0, 'Order_WaxB0sS5', 'Trade_ZUXL9jJA']\n",
      "receive deal\n",
      "3426.597500000047\n",
      "NOT ENOUGH MONEY FOR Order_WaxB0sS5\n",
      "['JCSC_EXAMPLE', '2018-04-10 00:00:00', '2018-04-10 00:00:00', '000977', None, -1, 23.11, 23.11006899465, 'trade_success', 1000.0, 1000.0, 23150.511615390635, 0, 'Order_uBIcK0wm', 'Trade_yNt9xFYr']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-04-10 00:00:00', '2018-04-10 00:00:00', '002417', None, -1, 11.54, 11.535, 'trade_success', 1000.0, 1000.0, 11557.3025, 0, 'Order_fdaLceFC', 'Trade_qX2fw5Zl']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-04-10 00:00:00', '2018-04-10 00:00:00', '300229', None, 1, 15.73, 15.73, 'trade_success', 1000, 1000, 15735.0, 0, 'Order_2Xd4mFic', 'Trade_hswvax96']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-04-10 00:00:00', '2018-04-10 00:00:00', '300738', None, -1, 75.47, 75.47, 'trade_success', 1000.0, 1000.0, 75602.0725, 0, 'Order_xcRyEmrk', 'Trade_TwYEylLX']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-04-11 00:00:00', '2018-04-11 00:00:00', '300245', None, 1, 13.6, 13.6, 'trade_success', 1000, 1000, 13605.0, 0, 'Order_zpNnR8AS', 'Trade_hyBgMGsn']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-04-11 00:00:00', '2018-04-11 00:00:00', '300365', None, -1, 21.89, 21.8934533703, 'trade_success', 1000.0, 1000.0, 21931.766913698026, 0, 'Order_y5ebkpIZ', 'Trade_r7qdEzAD']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-04-11 00:00:00', '2018-04-11 00:00:00', '600595', None, 1, 4.15, 4.15, 'trade_success', 1000, 1000, 4155.0, 0, 'Order_nzc65YOQ', 'Trade_zE42oYXL']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-04-11 00:00:00', '2018-04-11 00:00:00', '600770', None, 1, 7.29, 7.29, 'trade_success', 1000, 1000, 7295.0, 0, 'Order_LlS7TDoh', 'Trade_MsKAunv7']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-04-11 00:00:00', '2018-04-11 00:00:00', '600845', None, 1, 27.67, 27.6690938056, 'trade_success', 1000, 1000, 27676.011079051397, 0, 'Order_vX2gtbfd', 'Trade_FOP5vw3B']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-04-11 00:00:00', '2018-04-11 00:00:00', '600996', None, 1, 9.28, 9.28, 'trade_success', 1000, 1000, 9285.0, 0, 'Order_Qfi1GCaE', 'Trade_Vf0W6esF']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-04-11 00:00:00', '2018-04-11 00:00:00', '601360', None, 1, 41.58, 41.58, 'trade_success', 1000, 1000, 41590.395, 0, 'Order_dftrwzbg', 'Trade_aVSIdgLz']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-04-11 00:00:00', '2018-04-11 00:00:00', '601928', None, 1, 7.39, 7.39, 'trade_success', 1000, 1000, 7395.0, 0, 'Order_J12VC4ij', 'Trade_YcLKHZr6']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-04-12 00:00:00', '2018-04-12 00:00:00', '600198', None, 1, 8.32, 8.32, 'trade_success', 1000, 1000, 8325.0, 0, 'Order_pjNsHFm5', 'Trade_EegbuLDp']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-04-12 00:00:00', '2018-04-12 00:00:00', '600385', None, 1, 13.1, 13.1, 'trade_success', 1000, 1000, 13105.0, 0, 'Order_o5CHvtzR', 'Trade_4OvrGM5i']\n",
      "receive deal\n",
      "421.34750000004897\n",
      "NOT ENOUGH MONEY FOR Order_o5CHvtzR\n",
      "['JCSC_EXAMPLE', '2018-04-12 00:00:00', '2018-04-12 00:00:00', '603003', None, 1, 11.98, 11.98, 'trade_success', 1000, 1000, 11985.0, 0, 'Order_t13km9NM', 'Trade_eB4t8kQG']\n",
      "receive deal\n",
      "421.34750000004897\n",
      "NOT ENOUGH MONEY FOR Order_t13km9NM\n",
      "['JCSC_EXAMPLE', '2018-04-13 00:00:00', '2018-04-13 00:00:00', '002642', None, 1, 14.01, 14.01, 'trade_success', 1000, 1000, 14015.0, 0, 'Order_GWxZsKnI', 'Trade_UQvroJZS']\n",
      "receive deal\n",
      "421.34750000004897\n",
      "NOT ENOUGH MONEY FOR Order_GWxZsKnI\n",
      "['JCSC_EXAMPLE', '2018-04-13 00:00:00', '2018-04-13 00:00:00', '300020', None, 1, 11.89, 11.89, 'trade_success', 1000, 1000, 11895.0, 0, 'Order_rwPKjFd4', 'Trade_bhTLESHg']\n",
      "receive deal\n",
      "421.34750000004897\n",
      "NOT ENOUGH MONEY FOR Order_rwPKjFd4\n",
      "['JCSC_EXAMPLE', '2018-04-13 00:00:00', '2018-04-13 00:00:00', '300052', None, 1, 14.78, 14.78, 'trade_success', 1000, 1000, 14785.0, 0, 'Order_thXUIPDo', 'Trade_jQwirKI1']\n",
      "receive deal\n",
      "421.34750000004897\n",
      "NOT ENOUGH MONEY FOR Order_thXUIPDo\n",
      "['JCSC_EXAMPLE', '2018-04-13 00:00:00', '2018-04-13 00:00:00', '300085', None, -1, 16.34, 16.34, 'trade_success', 1000.0, 1000.0, 16369.51, 0, 'Order_g3w6Eir7', 'Trade_EMkD2TFQ']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-04-13 00:00:00', '2018-04-13 00:00:00', '300287', None, 1, 9.8, 9.8, 'trade_success', 1000, 1000, 9805.0, 0, 'Order_vi4usBEU', 'Trade_VUzIvBMy']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-04-13 00:00:00', '2018-04-13 00:00:00', '300383', None, -1, 17.75, 17.75086570055, 'trade_success', 1000.0, 1000.0, 17782.49199910083, 0, 'Order_avKOAeWI', 'Trade_qRrXk4dI']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-04-13 00:00:00', '2018-04-13 00:00:00', '600589', None, 1, 5.47, 5.47, 'trade_success', 1000, 1000, 5475.0, 0, 'Order_kLGItRjr', 'Trade_nfS9TvrQ']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-04-13 00:00:00', '2018-04-13 00:00:00', '600590', None, 1, 12.11, 12.11, 'trade_success', 1000, 1000, 12115.0, 0, 'Order_E2Vx6M3o', 'Trade_8adng0Ew']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-04-13 00:00:00', '2018-04-13 00:00:00', '600850', None, 1, 18.8, 18.8, 'trade_success', 1000, 1000, 18805.0, 0, 'Order_H6ycfYjJ', 'Trade_NSLG8rkB']\n",
      "receive deal\n",
      "7143.090000000046\n",
      "NOT ENOUGH MONEY FOR Order_H6ycfYjJ\n",
      "['JCSC_EXAMPLE', '2018-04-13 00:00:00', '2018-04-13 00:00:00', '601928', None, -1, 7.27, 7.265000000000001, 'trade_success', 1000.0, 1000.0, 7280.897500000001, 0, 'Order_XLp31JS6', 'Trade_OHL23E8g']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-04-16 00:00:00', '2018-04-16 00:00:00', '002065', None, 1, 8.4, 8.4, 'trade_success', 1000, 1000, 8405.0, 0, 'Order_ubHjJ3Tr', 'Trade_CvUZ3WIi']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-04-16 00:00:00', '2018-04-16 00:00:00', '002439', None, 1, 27.62, 27.6207787762, 'trade_success', 1000, 1000, 27627.68397089405, 0, 'Order_DwlsuhHa', 'Trade_knIG7tOU']\n",
      "receive deal\n",
      "6011.112500000045\n",
      "NOT ENOUGH MONEY FOR Order_DwlsuhHa\n",
      "['JCSC_EXAMPLE', '2018-04-16 00:00:00', '2018-04-16 00:00:00', '002456', None, 1, 21.11, 21.11, 'trade_success', 1000, 1000, 21115.2775, 0, 'Order_bkrNZPGC', 'Trade_4wyY7spB']\n",
      "receive deal\n",
      "6011.112500000045\n",
      "NOT ENOUGH MONEY FOR Order_bkrNZPGC\n",
      "['JCSC_EXAMPLE', '2018-04-16 00:00:00', '2018-04-16 00:00:00', '300085', None, 1, 17.58, 17.58, 'trade_success', 1000, 1000, 17585.0, 0, 'Order_wtyhXiU9', 'Trade_UpG5bvFx']\n",
      "receive deal\n",
      "6011.112500000045\n",
      "NOT ENOUGH MONEY FOR Order_wtyhXiU9\n",
      "['JCSC_EXAMPLE', '2018-04-16 00:00:00', '2018-04-16 00:00:00', '300113', None, 1, 22.66, 22.66, 'trade_success', 1000, 1000, 22665.665, 0, 'Order_rpDwfAdR', 'Trade_JXiZWD24']\n",
      "receive deal\n",
      "6011.112500000045\n",
      "NOT ENOUGH MONEY FOR Order_rpDwfAdR\n",
      "['JCSC_EXAMPLE', '2018-04-16 00:00:00', '2018-04-16 00:00:00', '300188', None, 1, 32.27, 32.27, 'trade_success', 1000, 1000, 32278.067500000005, 0, 'Order_ULXHCjAo', 'Trade_ymA1k72P']\n",
      "receive deal\n",
      "6011.112500000045\n",
      "NOT ENOUGH MONEY FOR Order_ULXHCjAo\n",
      "['JCSC_EXAMPLE', '2018-04-16 00:00:00', '2018-04-16 00:00:00', '300311', None, 1, 14.4, 14.4, 'trade_success', 1000, 1000, 14405.0, 0, 'Order_XCb8yVtU', 'Trade_uCmLt5xG']\n",
      "receive deal\n",
      "6011.112500000045\n",
      "NOT ENOUGH MONEY FOR Order_XCb8yVtU\n",
      "['JCSC_EXAMPLE', '2018-04-16 00:00:00', '2018-04-16 00:00:00', '600410', None, 1, 12.36, 12.36, 'trade_success', 1000, 1000, 12365.0, 0, 'Order_BMP3bpY9', 'Trade_zqoKYS6u']\n",
      "receive deal\n",
      "6011.112500000045\n",
      "NOT ENOUGH MONEY FOR Order_BMP3bpY9\n",
      "['JCSC_EXAMPLE', '2018-04-16 00:00:00', '2018-04-16 00:00:00', '600756', None, 1, 18.96, 18.96, 'trade_success', 1000, 1000, 18965.0, 0, 'Order_N3UOjK8k', 'Trade_YX3H2VWs']\n",
      "receive deal\n",
      "6011.112500000045\n",
      "NOT ENOUGH MONEY FOR Order_N3UOjK8k\n",
      "['JCSC_EXAMPLE', '2018-04-16 00:00:00', '2018-04-16 00:00:00', '600797', None, 1, 12.46, 12.46, 'trade_success', 1000, 1000, 12465.0, 0, 'Order_OlgByFbQ', 'Trade_DjEJuga4']\n",
      "receive deal\n",
      "6011.112500000045\n",
      "NOT ENOUGH MONEY FOR Order_OlgByFbQ\n",
      "['JCSC_EXAMPLE', '2018-04-17 00:00:00', '2018-04-17 00:00:00', '000977', None, 1, 24.98, 24.9768434664, 'trade_success', 1000, 1000, 24983.087677266598, 0, 'Order_HWENtI3C', 'Trade_lM0IAXne']\n",
      "receive deal\n",
      "6011.112500000045\n",
      "NOT ENOUGH MONEY FOR Order_HWENtI3C\n",
      "['JCSC_EXAMPLE', '2018-04-17 00:00:00', '2018-04-17 00:00:00', '300287', None, -1, 9.56, 9.56, 'trade_success', 1000.0, 1000.0, 9579.34, 0, 'Order_myObDLoh', 'Trade_ru0Jb2Re']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-04-17 00:00:00', '2018-04-17 00:00:00', '600589', None, -1, 5.37, 5.369999999999999, 'trade_success', 1000.0, 1000.0, 5383.054999999999, 0, 'Order_fzOQt846', 'Trade_0kEW6oJ2']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-04-17 00:00:00', '2018-04-17 00:00:00', '600770', None, -1, 7.12, 7.125, 'trade_success', 1000.0, 1000.0, 7140.6875, 0, 'Order_Ae5XduIP', 'Trade_IESLK0XA']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-04-18 00:00:00', '2018-04-18 00:00:00', '000938', None, 1, 79.42, 79.42, 'trade_success', 1000, 1000, 79439.855, 0, 'Order_ZL3jCpIk', 'Trade_4wjTg8pZ']\n",
      "receive deal\n",
      "28099.700000000044\n",
      "NOT ENOUGH MONEY FOR Order_ZL3jCpIk\n",
      "['JCSC_EXAMPLE', '2018-04-18 00:00:00', '2018-04-18 00:00:00', '002281', None, 1, 29.64, 29.64, 'trade_success', 1000, 1000, 29647.41, 0, 'Order_1PCUwZ56', 'Trade_L8kCSdVb']\n",
      "receive deal\n",
      "28099.700000000044\n",
      "NOT ENOUGH MONEY FOR Order_1PCUwZ56\n",
      "['JCSC_EXAMPLE', '2018-04-18 00:00:00', '2018-04-18 00:00:00', '002439', None, 1, 28.6, 28.598682071, 'trade_success', 1000, 1000, 28605.831741517748, 0, 'Order_eGDgpV6L', 'Trade_N0UapbdZ']\n",
      "receive deal\n",
      "28099.700000000044\n",
      "NOT ENOUGH MONEY FOR Order_eGDgpV6L\n",
      "['JCSC_EXAMPLE', '2018-04-18 00:00:00', '2018-04-18 00:00:00', '002463', None, 1, 4.35, 4.3511111111, 'trade_success', 1000, 1000, 4356.1111111, 0, 'Order_X7xe5kOH', 'Trade_QbKd7WvO']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-04-18 00:00:00', '2018-04-18 00:00:00', '300051', None, 1, 12.0, 12.0, 'trade_success', 1000, 1000, 12005.0, 0, 'Order_pcYyubnM', 'Trade_0LivO9mh']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-04-18 00:00:00', '2018-04-18 00:00:00', '300271', None, 1, 20.85, 20.85, 'trade_success', 1000, 1000, 20855.2125, 0, 'Order_vfJxWIqH', 'Trade_LPiNh9Rb']\n",
      "receive deal\n",
      "11721.087500000045\n",
      "NOT ENOUGH MONEY FOR Order_vfJxWIqH\n",
      "['JCSC_EXAMPLE', '2018-04-18 00:00:00', '2018-04-18 00:00:00', '300302', None, 1, 14.94, 14.94, 'trade_success', 1000, 1000, 14945.0, 0, 'Order_v5toJjW6', 'Trade_385kFcTO']\n",
      "receive deal\n",
      "11721.087500000045\n",
      "NOT ENOUGH MONEY FOR Order_v5toJjW6\n",
      "['JCSC_EXAMPLE', '2018-04-18 00:00:00', '2018-04-18 00:00:00', '600100', None, 1, 10.74, 10.74, 'trade_success', 1000, 1000, 10745.0, 0, 'Order_fR1zVgNU', 'Trade_78JQ2XyC']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-04-18 00:00:00', '2018-04-18 00:00:00', '600770', None, 1, 7.51, 7.51, 'trade_success', 1000, 1000, 7515.0, 0, 'Order_Ul24jnDe', 'Trade_LTrS1ZN0']\n",
      "receive deal\n",
      "962.292500000045\n",
      "NOT ENOUGH MONEY FOR Order_Ul24jnDe\n",
      "['JCSC_EXAMPLE', '2018-04-18 00:00:00', '2018-04-18 00:00:00', '600850', None, 1, 19.6, 19.6, 'trade_success', 1000, 1000, 19605.0, 0, 'Order_VJTc106m', 'Trade_Asgl7Ont']\n",
      "receive deal\n",
      "962.292500000045\n",
      "NOT ENOUGH MONEY FOR Order_VJTc106m\n",
      "['JCSC_EXAMPLE', '2018-04-18 00:00:00', '2018-04-18 00:00:00', '603019', None, 1, 57.87, 57.8695198171, 'trade_success', 1000, 1000, 57883.98719705427, 0, 'Order_RW2PoNmC', 'Trade_CGHw8dKe']\n",
      "receive deal\n",
      "962.292500000045\n",
      "NOT ENOUGH MONEY FOR Order_RW2PoNmC\n",
      "['JCSC_EXAMPLE', '2018-04-19 00:00:00', '2018-04-19 00:00:00', '002544', None, 1, 17.42, 17.42, 'trade_success', 1000, 1000, 17425.0, 0, 'Order_tXxyE3NK', 'Trade_dopkwQGl']\n",
      "receive deal\n",
      "962.292500000045\n",
      "NOT ENOUGH MONEY FOR Order_tXxyE3NK\n",
      "['JCSC_EXAMPLE', '2018-04-19 00:00:00', '2018-04-19 00:00:00', '300017', None, 1, 14.85, 14.85, 'trade_success', 1000, 1000, 14855.0, 0, 'Order_UZ6ABg9S', 'Trade_ydmSXwcb']\n",
      "receive deal\n",
      "962.292500000045\n",
      "NOT ENOUGH MONEY FOR Order_UZ6ABg9S\n",
      "['JCSC_EXAMPLE', '2018-04-19 00:00:00', '2018-04-19 00:00:00', '300366', None, 1, 12.2, 12.2, 'trade_success', 1000, 1000, 12205.0, 0, 'Order_Um3vMr91', 'Trade_wuhjOt6Z']\n",
      "receive deal\n",
      "962.292500000045\n",
      "NOT ENOUGH MONEY FOR Order_Um3vMr91\n",
      "['JCSC_EXAMPLE', '2018-04-19 00:00:00', '2018-04-19 00:00:00', '300369', None, 1, 14.65, 14.65, 'trade_success', 1000, 1000, 14655.0, 0, 'Order_jMEntxNG', 'Trade_dzNT0o75']\n",
      "receive deal\n",
      "962.292500000045\n",
      "NOT ENOUGH MONEY FOR Order_jMEntxNG\n",
      "['JCSC_EXAMPLE', '2018-04-19 00:00:00', '2018-04-19 00:00:00', '600410', None, 1, 12.58, 12.58, 'trade_success', 1000, 1000, 12585.0, 0, 'Order_qNDS7Fyj', 'Trade_B53MF1CX']\n",
      "receive deal\n",
      "962.292500000045\n",
      "NOT ENOUGH MONEY FOR Order_qNDS7Fyj\n",
      "['JCSC_EXAMPLE', '2018-04-19 00:00:00', '2018-04-19 00:00:00', '600797', None, 1, 12.56, 12.56, 'trade_success', 1000, 1000, 12565.0, 0, 'Order_aKPqZLEm', 'Trade_houd0wPG']\n",
      "receive deal\n",
      "962.292500000045\n",
      "NOT ENOUGH MONEY FOR Order_aKPqZLEm\n",
      "['JCSC_EXAMPLE', '2018-04-20 00:00:00', '2018-04-20 00:00:00', '000948', None, 1, 11.42, 11.42, 'trade_success', 1000, 1000, 11425.0, 0, 'Order_TMbP8pYH', 'Trade_5SyqIfm8']\n",
      "receive deal\n",
      "962.292500000045\n",
      "NOT ENOUGH MONEY FOR Order_TMbP8pYH\n",
      "['JCSC_EXAMPLE', '2018-04-20 00:00:00', '2018-04-20 00:00:00', '300051', None, -1, 11.29, 11.295, 'trade_success', 1000.0, 1000.0, 11316.9425, 0, 'Order_7g6uwcl4', 'Trade_2VrMymkX']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-04-20 00:00:00', '2018-04-20 00:00:00', '600589', None, 1, 5.47, 5.47, 'trade_success', 1000, 1000, 5475.0, 0, 'Order_p5UcQmBw', 'Trade_UObCYmsv']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-04-20 00:00:00', '2018-04-20 00:00:00', '600590', None, -1, 11.29, 11.285, 'trade_success', 1000.0, 1000.0, 11306.9275, 0, 'Order_img5TnKy', 'Trade_lud8hbGt']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-04-20 00:00:00', '2018-04-20 00:00:00', '600601', None, 1, 3.09, 3.09, 'trade_success', 1000, 1000, 3095.0, 0, 'Order_dI9SJy3q', 'Trade_eDEzK6pc']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-04-23 00:00:00', '2018-04-23 00:00:00', '300366', None, 1, 12.45, 12.45, 'trade_success', 1000, 1000, 12455.0, 0, 'Order_k2rIMafR', 'Trade_o4aEF1eT']\n",
      "receive deal\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['JCSC_EXAMPLE', '2018-04-23 00:00:00', '2018-04-23 00:00:00', '600601', None, -1, 3.08, 3.075, 'trade_success', 1000.0, 1000.0, 3084.6125, 0, 'Order_dtTBM43Y', 'Trade_wPmDI0Zn']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-04-24 00:00:00', '2018-04-24 00:00:00', '000948', None, 1, 11.59, 11.59, 'trade_success', 1000, 1000, 11595.0, 0, 'Order_CdiZN1Of', 'Trade_pSFE5gtI']\n",
      "receive deal\n",
      "5620.430000000044\n",
      "NOT ENOUGH MONEY FOR Order_CdiZN1Of\n",
      "['JCSC_EXAMPLE', '2018-04-24 00:00:00', '2018-04-24 00:00:00', '300274', None, 1, 18.79, 18.79, 'trade_success', 1000, 1000, 18795.0, 0, 'Order_rs4xkhe5', 'Trade_VtPGXMBf']\n",
      "receive deal\n",
      "5620.430000000044\n",
      "NOT ENOUGH MONEY FOR Order_rs4xkhe5\n",
      "['JCSC_EXAMPLE', '2018-04-24 00:00:00', '2018-04-24 00:00:00', '600601', None, 1, 3.08, 3.08, 'trade_success', 1000, 1000, 3085.0, 0, 'Order_xrFNEVC4', 'Trade_nN2dklEI']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-04-25 00:00:00', '2018-04-25 00:00:00', '002197', None, 1, 10.35, 10.35, 'trade_success', 1000, 1000, 10355.0, 0, 'Order_k32HOdrc', 'Trade_LbNuXCHy']\n",
      "receive deal\n",
      "2535.040000000044\n",
      "NOT ENOUGH MONEY FOR Order_k32HOdrc\n",
      "['JCSC_EXAMPLE', '2018-04-25 00:00:00', '2018-04-25 00:00:00', '002315', None, 1, 20.9, 20.9, 'trade_success', 1000, 1000, 20905.225, 0, 'Order_eP2VlhIZ', 'Trade_SHWf6uRP']\n",
      "receive deal\n",
      "2535.040000000044\n",
      "NOT ENOUGH MONEY FOR Order_eP2VlhIZ\n",
      "['JCSC_EXAMPLE', '2018-04-25 00:00:00', '2018-04-25 00:00:00', '300044', None, 1, 10.52, 10.5166520237, 'trade_success', 1000, 1000, 10521.6520237, 0, 'Order_Bwto2Qh5', 'Trade_uoeWO6Jx']\n",
      "receive deal\n",
      "2535.040000000044\n",
      "NOT ENOUGH MONEY FOR Order_Bwto2Qh5\n",
      "['JCSC_EXAMPLE', '2018-04-25 00:00:00', '2018-04-25 00:00:00', '300168', None, 1, 19.0, 19.0, 'trade_success', 1000, 1000, 19005.0, 0, 'Order_VvlzHuPk', 'Trade_BIny4ezk']\n",
      "receive deal\n",
      "2535.040000000044\n",
      "NOT ENOUGH MONEY FOR Order_VvlzHuPk\n",
      "['JCSC_EXAMPLE', '2018-04-25 00:00:00', '2018-04-25 00:00:00', '600845', None, -1, 30.0, 30.0013736393, 'trade_success', 1000.0, 1000.0, 30053.876043168777, 0, 'Order_qm1vYekP', 'Trade_ZjCY1fkt']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-04-26 00:00:00', '2018-04-26 00:00:00', '000066', None, -1, 9.28, 9.280000000000001, 'trade_success', 1000.0, 1000.0, 9298.920000000002, 0, 'Order_Q5H2Fkrm', 'Trade_FJcA7hXZ']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-04-26 00:00:00', '2018-04-26 00:00:00', '000611', None, 1, 7.56, 7.56, 'trade_success', 1000, 1000, 7565.0, 0, 'Order_5vLmotrf', 'Trade_WmjPUt71']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-04-26 00:00:00', '2018-04-26 00:00:00', '000836', None, 1, 4.56, 4.56, 'trade_success', 1000, 1000, 4565.0, 0, 'Order_8c0vIeK3', 'Trade_hErnzktf']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-04-26 00:00:00', '2018-04-26 00:00:00', '002063', None, 1, 11.72, 11.72, 'trade_success', 1000, 1000, 11725.0, 0, 'Order_v26iRnZQ', 'Trade_7DL3ticJ']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-04-26 00:00:00', '2018-04-26 00:00:00', '002544', None, 1, 18.22, 18.22, 'trade_success', 1000, 1000, 18225.0, 0, 'Order_YUEAjRpT', 'Trade_XrIvnj9M']\n",
      "receive deal\n",
      "18002.06000000005\n",
      "NOT ENOUGH MONEY FOR Order_YUEAjRpT\n",
      "['JCSC_EXAMPLE', '2018-04-26 00:00:00', '2018-04-26 00:00:00', '002657', None, 1, 20.79, 20.79, 'trade_success', 1000, 1000, 20795.1975, 0, 'Order_4iyPkT7G', 'Trade_uml7NVE9']\n",
      "receive deal\n",
      "18002.06000000005\n",
      "NOT ENOUGH MONEY FOR Order_4iyPkT7G\n",
      "['JCSC_EXAMPLE', '2018-04-26 00:00:00', '2018-04-26 00:00:00', '300025', None, 1, 5.07, 5.07, 'trade_success', 1000, 1000, 5075.0, 0, 'Order_U1mKR6OG', 'Trade_lsQAmCX7']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-04-26 00:00:00', '2018-04-26 00:00:00', '300235', None, 1, 12.37, 12.37, 'trade_success', 1000, 1000, 12375.0, 0, 'Order_8HUWfJx1', 'Trade_IXablmFz']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-04-27 00:00:00', '2018-04-27 00:00:00', '002063', None, -1, 11.64, 11.645, 'trade_success', 1000.0, 1000.0, 11667.4675, 0, 'Order_BtPZvUWw', 'Trade_vFC1unky']\n",
      "receive deal\n",
      "['JCSC_EXAMPLE', '2018-04-27 00:00:00', '2018-04-27 00:00:00', '300052', None, 1, 14.34, 14.34, 'trade_success', 1000, 1000, 14345.0, 0, 'Order_bWpP4RqX', 'Trade_7ipd34O8']\n",
      "receive deal\n",
      "12191.910000000049\n",
      "NOT ENOUGH MONEY FOR Order_bWpP4RqX\n",
      "['JCSC_EXAMPLE', '2018-04-27 00:00:00', '2018-04-27 00:00:00', '601360', None, -1, 37.8, 37.805, 'trade_success', 1000.0, 1000.0, 37871.158749999995, 0, 'Order_lyDrw7iT', 'Trade_NyfhbLEi']\n",
      "receive deal\n"
     ]
    }
   ],
   "source": [
    "data_forbacktest=data.select_time('2018-01-01','2018-05-01')\n",
    "\n",
    "\n",
    "for items in data_forbacktest.panel_gen:\n",
    "    for item in items.security_gen:\n",
    "        daily_ind=ind.loc[item.index]\n",
    "        if daily_ind.CROSS_JC.iloc[0]>0:\n",
    "            order=Account.send_order(\n",
    "                code=item.code[0], \n",
    "                time=item.date[0], \n",
    "                amount=1000, \n",
    "                towards=QA.ORDER_DIRECTION.BUY, \n",
    "                price=0, \n",
    "                order_model=QA.ORDER_MODEL.CLOSE, \n",
    "                amount_model=QA.AMOUNT_MODEL.BY_AMOUNT\n",
    "                )\n",
    "            #print(item.to_json()[0])\n",
    "            Broker.receive_order(QA.QA_Event(order=order,market_data=item))\n",
    "            \n",
    "            \n",
    "            trade_mes=Broker.query_orders(Account.account_cookie,'filled')\n",
    "            res=trade_mes.loc[order.account_cookie,order.realorder_id]\n",
    "            order.trade(res.trade_id,res.trade_price,res.trade_amount,res.trade_time)\n",
    "        elif daily_ind.CROSS_SC.iloc[0]>0:\n",
    "            if Account.sell_available.get(item.code[0], 0)>0:\n",
    "                order=Account.send_order(\n",
    "                    code=item.code[0], \n",
    "                    time=item.date[0], \n",
    "                    amount=Account.sell_available.get(item.code[0], 0), \n",
    "                    towards=QA.ORDER_DIRECTION.SELL, \n",
    "                    price=0, \n",
    "                    order_model=QA.ORDER_MODEL.MARKET, \n",
    "                    amount_model=QA.AMOUNT_MODEL.BY_AMOUNT\n",
    "                    )\n",
    "                Broker.receive_order(QA.QA_Event(order=order,market_data=item))\n",
    "\n",
    "\n",
    "                trade_mes=Broker.query_orders(Account.account_cookie,'filled')\n",
    "                res=trade_mes.loc[order.account_cookie,order.realorder_id]\n",
    "                order.trade(res.trade_id,res.trade_price,res.trade_amount,res.trade_time)\n",
    "    Account.settle()\n",
    "            \n",
    "        #break"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## STEP5: 分析账户"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[['2018-01-02 00:00:00',\n",
       "  '002195',\n",
       "  5.91,\n",
       "  1000,\n",
       "  194079.6575,\n",
       "  'Order_AGZefuXd',\n",
       "  'Order_AGZefuXd',\n",
       "  'Trade_7RxnPTq1',\n",
       "  'JCSC_EXAMPLE',\n",
       "  1.4775,\n",
       "  8.865],\n",
       " ['2018-01-02 00:00:00',\n",
       "  '002456',\n",
       "  20.78,\n",
       "  1000,\n",
       "  173263.2925,\n",
       "  'Order_qOuEB4fo',\n",
       "  'Order_qOuEB4fo',\n",
       "  'Trade_5IZEW2LB',\n",
       "  'JCSC_EXAMPLE',\n",
       "  5.195,\n",
       "  31.17],\n",
       " ['2018-01-02 00:00:00',\n",
       "  '002544',\n",
       "  15.85,\n",
       "  1000,\n",
       "  157385.55500000002,\n",
       "  'Order_ripYwt6L',\n",
       "  'Order_ripYwt6L',\n",
       "  'Trade_VzvpFjPM',\n",
       "  'JCSC_EXAMPLE',\n",
       "  3.9625,\n",
       "  23.775000000000002],\n",
       " ['2018-01-02 00:00:00',\n",
       "  '300290',\n",
       "  8.71,\n",
       "  1000,\n",
       "  148660.31250000003,\n",
       "  'Order_ph50Tje9',\n",
       "  'Order_ph50Tje9',\n",
       "  'Trade_vWYaMmhq',\n",
       "  'JCSC_EXAMPLE',\n",
       "  2.1775,\n",
       "  13.065],\n",
       " ['2018-01-02 00:00:00',\n",
       "  '300367',\n",
       "  15.39,\n",
       "  1000,\n",
       "  133243.38000000003,\n",
       "  'Order_YvlByWfD',\n",
       "  'Order_YvlByWfD',\n",
       "  'Trade_zWlyg0UM',\n",
       "  'JCSC_EXAMPLE',\n",
       "  3.8475,\n",
       "  23.085],\n",
       " ['2018-01-02 00:00:00',\n",
       "  '600105',\n",
       "  6.58,\n",
       "  1000,\n",
       "  126651.86500000003,\n",
       "  'Order_8sBTIvLO',\n",
       "  'Order_8sBTIvLO',\n",
       "  'Trade_cay7rZ6J',\n",
       "  'JCSC_EXAMPLE',\n",
       "  1.645,\n",
       "  9.870000000000001],\n",
       " ['2018-01-02 00:00:00',\n",
       "  '600797',\n",
       "  11.87,\n",
       "  1000,\n",
       "  114761.09250000003,\n",
       "  'Order_whQIWHBi',\n",
       "  'Order_whQIWHBi',\n",
       "  'Trade_NtWVGFSo',\n",
       "  'JCSC_EXAMPLE',\n",
       "  2.9675000000000002,\n",
       "  17.805],\n",
       " ['2018-01-03 00:00:00',\n",
       "  '000070',\n",
       "  9.52,\n",
       "  1000,\n",
       "  105224.43250000002,\n",
       "  'Order_wDPTJiRh',\n",
       "  'Order_wDPTJiRh',\n",
       "  'Trade_eufovKcX',\n",
       "  'JCSC_EXAMPLE',\n",
       "  2.38,\n",
       "  14.280000000000001],\n",
       " ['2018-01-03 00:00:00',\n",
       "  '000100',\n",
       "  3.99,\n",
       "  1000,\n",
       "  101227.45000000003,\n",
       "  'Order_f8yNTPHe',\n",
       "  'Order_f8yNTPHe',\n",
       "  'Trade_OUEDoFnu',\n",
       "  'JCSC_EXAMPLE',\n",
       "  0.9975,\n",
       "  5.985],\n",
       " ['2018-01-03 00:00:00',\n",
       "  '002065',\n",
       "  8.53,\n",
       "  1000,\n",
       "  92682.52250000002,\n",
       "  'Order_x5k8PvbA',\n",
       "  'Order_x5k8PvbA',\n",
       "  'Trade_dBbge5v4',\n",
       "  'JCSC_EXAMPLE',\n",
       "  2.1325,\n",
       "  12.795],\n",
       " ['2018-01-03 00:00:00',\n",
       "  '002335',\n",
       "  30.04,\n",
       "  1000,\n",
       "  62589.95250000002,\n",
       "  'Order_jKYkEcmX',\n",
       "  'Order_jKYkEcmX',\n",
       "  'Trade_L1dMti6K',\n",
       "  'JCSC_EXAMPLE',\n",
       "  7.51,\n",
       "  45.06],\n",
       " ['2018-01-03 00:00:00',\n",
       "  '300036',\n",
       "  15.78,\n",
       "  1000,\n",
       "  46782.33750000002,\n",
       "  'Order_iB3KzEPv',\n",
       "  'Order_iB3KzEPv',\n",
       "  'Trade_rXCb1PJu',\n",
       "  'JCSC_EXAMPLE',\n",
       "  3.9450000000000003,\n",
       "  23.67],\n",
       " ['2018-01-03 00:00:00',\n",
       "  '600198',\n",
       "  11.65,\n",
       "  1000,\n",
       "  35111.950000000026,\n",
       "  'Order_eFZH05bs',\n",
       "  'Order_eFZH05bs',\n",
       "  'Trade_nHqFwT30',\n",
       "  'JCSC_EXAMPLE',\n",
       "  2.9125,\n",
       "  17.475],\n",
       " ['2018-01-03 00:00:00',\n",
       "  '600718',\n",
       "  15.0,\n",
       "  1000,\n",
       "  20085.700000000026,\n",
       "  'Order_K3MjyXZo',\n",
       "  'Order_K3MjyXZo',\n",
       "  'Trade_zrGbK97E',\n",
       "  'JCSC_EXAMPLE',\n",
       "  3.75,\n",
       "  22.5],\n",
       " ['2018-01-03 00:00:00',\n",
       "  '600804',\n",
       "  17.93,\n",
       "  1000,\n",
       "  2124.3225000000275,\n",
       "  'Order_EdD6u1Cb',\n",
       "  'Order_EdD6u1Cb',\n",
       "  'Trade_Bw0n39H5',\n",
       "  'JCSC_EXAMPLE',\n",
       "  4.4825,\n",
       "  26.895],\n",
       " ['2018-01-09 00:00:00',\n",
       "  '300367',\n",
       "  14.91,\n",
       "  -1000,\n",
       "  17060.41500000003,\n",
       "  'Order_KYdA3NQ9',\n",
       "  'Order_KYdA3NQ9',\n",
       "  'Trade_rf1oEbiF',\n",
       "  'JCSC_EXAMPLE',\n",
       "  -3.7275,\n",
       "  -22.365000000000002],\n",
       " ['2018-01-10 00:00:00',\n",
       "  '300245',\n",
       "  13.8,\n",
       "  1000,\n",
       "  3236.2650000000303,\n",
       "  'Order_uCE5pWke',\n",
       "  'Order_uCE5pWke',\n",
       "  'Trade_ZGCEmfb8',\n",
       "  'JCSC_EXAMPLE',\n",
       "  3.45,\n",
       "  20.7],\n",
       " ['2018-01-12 00:00:00',\n",
       "  '002456',\n",
       "  19.84,\n",
       "  -1000,\n",
       "  23110.98500000003,\n",
       "  'Order_p5J1Paxo',\n",
       "  'Order_p5J1Paxo',\n",
       "  'Trade_1quYOxnZ',\n",
       "  'JCSC_EXAMPLE',\n",
       "  -4.96,\n",
       "  -29.76],\n",
       " ['2018-01-12 00:00:00',\n",
       "  '300052',\n",
       "  15.85,\n",
       "  1000,\n",
       "  7233.24750000003,\n",
       "  'Order_GOfSMKya',\n",
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       " ['2018-04-24 00:00:00',\n",
       "  '600601',\n",
       "  3.08,\n",
       "  1000,\n",
       "  2535.040000000044,\n",
       "  'Order_xrFNEVC4',\n",
       "  'Order_xrFNEVC4',\n",
       "  'Trade_BlUXpNAc',\n",
       "  'JCSC_EXAMPLE',\n",
       "  0.77,\n",
       "  4.62],\n",
       " ['2018-04-25 00:00:00',\n",
       "  '600845',\n",
       "  30.0,\n",
       "  -1000,\n",
       "  32587.540000000045,\n",
       "  'Order_qm1vYekP',\n",
       "  'Order_qm1vYekP',\n",
       "  'Trade_Z8PMI0wO',\n",
       "  'JCSC_EXAMPLE',\n",
       "  -7.5,\n",
       "  -45.0],\n",
       " ['2018-04-26 00:00:00',\n",
       "  '000066',\n",
       "  9.28,\n",
       "  -1000,\n",
       "  41883.78000000004,\n",
       "  'Order_Q5H2Fkrm',\n",
       "  'Order_Q5H2Fkrm',\n",
       "  'Trade_5kSnPrJ0',\n",
       "  'JCSC_EXAMPLE',\n",
       "  -2.32,\n",
       "  -13.92],\n",
       " ['2018-04-26 00:00:00',\n",
       "  '000611',\n",
       "  7.56,\n",
       "  1000,\n",
       "  34310.55000000005,\n",
       "  'Order_5vLmotrf',\n",
       "  'Order_5vLmotrf',\n",
       "  'Trade_9aXfk1ur',\n",
       "  'JCSC_EXAMPLE',\n",
       "  1.8900000000000001,\n",
       "  11.34],\n",
       " ['2018-04-26 00:00:00',\n",
       "  '000836',\n",
       "  4.56,\n",
       "  1000,\n",
       "  29742.570000000047,\n",
       "  'Order_8c0vIeK3',\n",
       "  'Order_8c0vIeK3',\n",
       "  'Trade_aez4PKrt',\n",
       "  'JCSC_EXAMPLE',\n",
       "  1.1400000000000001,\n",
       "  6.84],\n",
       " ['2018-04-26 00:00:00',\n",
       "  '002063',\n",
       "  11.72,\n",
       "  1000,\n",
       "  18002.06000000005,\n",
       "  'Order_v26iRnZQ',\n",
       "  'Order_v26iRnZQ',\n",
       "  'Trade_CtKujRbr',\n",
       "  'JCSC_EXAMPLE',\n",
       "  2.93,\n",
       "  17.580000000000002],\n",
       " ['2018-04-26 00:00:00',\n",
       "  '300025',\n",
       "  5.07,\n",
       "  1000,\n",
       "  12923.187500000047,\n",
       "  'Order_U1mKR6OG',\n",
       "  'Order_U1mKR6OG',\n",
       "  'Trade_18JMpRnG',\n",
       "  'JCSC_EXAMPLE',\n",
       "  1.2675,\n",
       "  7.605],\n",
       " ['2018-04-26 00:00:00',\n",
       "  '300235',\n",
       "  12.37,\n",
       "  1000,\n",
       "  531.5400000000482,\n",
       "  'Order_8HUWfJx1',\n",
       "  'Order_8HUWfJx1',\n",
       "  'Trade_WPNlvA1E',\n",
       "  'JCSC_EXAMPLE',\n",
       "  3.0925000000000002,\n",
       "  18.555],\n",
       " ['2018-04-27 00:00:00',\n",
       "  '002063',\n",
       "  11.64,\n",
       "  -1000,\n",
       "  12191.910000000049,\n",
       "  'Order_BtPZvUWw',\n",
       "  'Order_BtPZvUWw',\n",
       "  'Trade_ICkVoQOZ',\n",
       "  'JCSC_EXAMPLE',\n",
       "  -2.91,\n",
       "  -17.46],\n",
       " ['2018-04-27 00:00:00',\n",
       "  '601360',\n",
       "  37.8,\n",
       "  -1000,\n",
       "  50058.06000000005,\n",
       "  'Order_lyDrw7iT',\n",
       "  'Order_lyDrw7iT',\n",
       "  'Trade_3aozRWnk',\n",
       "  'JCSC_EXAMPLE',\n",
       "  -9.450000000000001,\n",
       "  -56.7]]"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Account.history"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>datetime</th>\n",
       "      <th>code</th>\n",
       "      <th>price</th>\n",
       "      <th>amount</th>\n",
       "      <th>cash</th>\n",
       "      <th>order_id</th>\n",
       "      <th>realorder_id</th>\n",
       "      <th>trade_id</th>\n",
       "      <th>account_cookie</th>\n",
       "      <th>commission</th>\n",
       "      <th>tax</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2018-01-02 00:00:00</td>\n",
       "      <td>002195</td>\n",
       "      <td>5.91</td>\n",
       "      <td>1000</td>\n",
       "      <td>194079.6575</td>\n",
       "      <td>Order_AGZefuXd</td>\n",
       "      <td>Order_AGZefuXd</td>\n",
       "      <td>Trade_7RxnPTq1</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>1.4775</td>\n",
       "      <td>8.865</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2018-01-02 00:00:00</td>\n",
       "      <td>002456</td>\n",
       "      <td>20.78</td>\n",
       "      <td>1000</td>\n",
       "      <td>173263.2925</td>\n",
       "      <td>Order_qOuEB4fo</td>\n",
       "      <td>Order_qOuEB4fo</td>\n",
       "      <td>Trade_5IZEW2LB</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>5.1950</td>\n",
       "      <td>31.170</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2018-01-02 00:00:00</td>\n",
       "      <td>002544</td>\n",
       "      <td>15.85</td>\n",
       "      <td>1000</td>\n",
       "      <td>157385.5550</td>\n",
       "      <td>Order_ripYwt6L</td>\n",
       "      <td>Order_ripYwt6L</td>\n",
       "      <td>Trade_VzvpFjPM</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>3.9625</td>\n",
       "      <td>23.775</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2018-01-02 00:00:00</td>\n",
       "      <td>300290</td>\n",
       "      <td>8.71</td>\n",
       "      <td>1000</td>\n",
       "      <td>148660.3125</td>\n",
       "      <td>Order_ph50Tje9</td>\n",
       "      <td>Order_ph50Tje9</td>\n",
       "      <td>Trade_vWYaMmhq</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>2.1775</td>\n",
       "      <td>13.065</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2018-01-02 00:00:00</td>\n",
       "      <td>300367</td>\n",
       "      <td>15.39</td>\n",
       "      <td>1000</td>\n",
       "      <td>133243.3800</td>\n",
       "      <td>Order_YvlByWfD</td>\n",
       "      <td>Order_YvlByWfD</td>\n",
       "      <td>Trade_zWlyg0UM</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>3.8475</td>\n",
       "      <td>23.085</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2018-01-02 00:00:00</td>\n",
       "      <td>600105</td>\n",
       "      <td>6.58</td>\n",
       "      <td>1000</td>\n",
       "      <td>126651.8650</td>\n",
       "      <td>Order_8sBTIvLO</td>\n",
       "      <td>Order_8sBTIvLO</td>\n",
       "      <td>Trade_cay7rZ6J</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>1.6450</td>\n",
       "      <td>9.870</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2018-01-02 00:00:00</td>\n",
       "      <td>600797</td>\n",
       "      <td>11.87</td>\n",
       "      <td>1000</td>\n",
       "      <td>114761.0925</td>\n",
       "      <td>Order_whQIWHBi</td>\n",
       "      <td>Order_whQIWHBi</td>\n",
       "      <td>Trade_NtWVGFSo</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>2.9675</td>\n",
       "      <td>17.805</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2018-01-03 00:00:00</td>\n",
       "      <td>000070</td>\n",
       "      <td>9.52</td>\n",
       "      <td>1000</td>\n",
       "      <td>105224.4325</td>\n",
       "      <td>Order_wDPTJiRh</td>\n",
       "      <td>Order_wDPTJiRh</td>\n",
       "      <td>Trade_eufovKcX</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>2.3800</td>\n",
       "      <td>14.280</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2018-01-03 00:00:00</td>\n",
       "      <td>000100</td>\n",
       "      <td>3.99</td>\n",
       "      <td>1000</td>\n",
       "      <td>101227.4500</td>\n",
       "      <td>Order_f8yNTPHe</td>\n",
       "      <td>Order_f8yNTPHe</td>\n",
       "      <td>Trade_OUEDoFnu</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>0.9975</td>\n",
       "      <td>5.985</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2018-01-03 00:00:00</td>\n",
       "      <td>002065</td>\n",
       "      <td>8.53</td>\n",
       "      <td>1000</td>\n",
       "      <td>92682.5225</td>\n",
       "      <td>Order_x5k8PvbA</td>\n",
       "      <td>Order_x5k8PvbA</td>\n",
       "      <td>Trade_dBbge5v4</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>2.1325</td>\n",
       "      <td>12.795</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2018-01-03 00:00:00</td>\n",
       "      <td>002335</td>\n",
       "      <td>30.04</td>\n",
       "      <td>1000</td>\n",
       "      <td>62589.9525</td>\n",
       "      <td>Order_jKYkEcmX</td>\n",
       "      <td>Order_jKYkEcmX</td>\n",
       "      <td>Trade_L1dMti6K</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>7.5100</td>\n",
       "      <td>45.060</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2018-01-03 00:00:00</td>\n",
       "      <td>300036</td>\n",
       "      <td>15.78</td>\n",
       "      <td>1000</td>\n",
       "      <td>46782.3375</td>\n",
       "      <td>Order_iB3KzEPv</td>\n",
       "      <td>Order_iB3KzEPv</td>\n",
       "      <td>Trade_rXCb1PJu</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>3.9450</td>\n",
       "      <td>23.670</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>2018-01-03 00:00:00</td>\n",
       "      <td>600198</td>\n",
       "      <td>11.65</td>\n",
       "      <td>1000</td>\n",
       "      <td>35111.9500</td>\n",
       "      <td>Order_eFZH05bs</td>\n",
       "      <td>Order_eFZH05bs</td>\n",
       "      <td>Trade_nHqFwT30</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>2.9125</td>\n",
       "      <td>17.475</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>2018-01-03 00:00:00</td>\n",
       "      <td>600718</td>\n",
       "      <td>15.00</td>\n",
       "      <td>1000</td>\n",
       "      <td>20085.7000</td>\n",
       "      <td>Order_K3MjyXZo</td>\n",
       "      <td>Order_K3MjyXZo</td>\n",
       "      <td>Trade_zrGbK97E</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>3.7500</td>\n",
       "      <td>22.500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>2018-01-03 00:00:00</td>\n",
       "      <td>600804</td>\n",
       "      <td>17.93</td>\n",
       "      <td>1000</td>\n",
       "      <td>2124.3225</td>\n",
       "      <td>Order_EdD6u1Cb</td>\n",
       "      <td>Order_EdD6u1Cb</td>\n",
       "      <td>Trade_Bw0n39H5</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>4.4825</td>\n",
       "      <td>26.895</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>2018-01-09 00:00:00</td>\n",
       "      <td>300367</td>\n",
       "      <td>14.91</td>\n",
       "      <td>-1000</td>\n",
       "      <td>17060.4150</td>\n",
       "      <td>Order_KYdA3NQ9</td>\n",
       "      <td>Order_KYdA3NQ9</td>\n",
       "      <td>Trade_rf1oEbiF</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>-3.7275</td>\n",
       "      <td>-22.365</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>2018-01-10 00:00:00</td>\n",
       "      <td>300245</td>\n",
       "      <td>13.80</td>\n",
       "      <td>1000</td>\n",
       "      <td>3236.2650</td>\n",
       "      <td>Order_uCE5pWke</td>\n",
       "      <td>Order_uCE5pWke</td>\n",
       "      <td>Trade_ZGCEmfb8</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>3.4500</td>\n",
       "      <td>20.700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>2018-01-12 00:00:00</td>\n",
       "      <td>002456</td>\n",
       "      <td>19.84</td>\n",
       "      <td>-1000</td>\n",
       "      <td>23110.9850</td>\n",
       "      <td>Order_p5J1Paxo</td>\n",
       "      <td>Order_p5J1Paxo</td>\n",
       "      <td>Trade_1quYOxnZ</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>-4.9600</td>\n",
       "      <td>-29.760</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>2018-01-12 00:00:00</td>\n",
       "      <td>300052</td>\n",
       "      <td>15.85</td>\n",
       "      <td>1000</td>\n",
       "      <td>7233.2475</td>\n",
       "      <td>Order_GOfSMKya</td>\n",
       "      <td>Order_GOfSMKya</td>\n",
       "      <td>Trade_PIZ23WAV</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>3.9625</td>\n",
       "      <td>23.775</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>2018-01-15 00:00:00</td>\n",
       "      <td>300036</td>\n",
       "      <td>14.49</td>\n",
       "      <td>-1000</td>\n",
       "      <td>21748.6050</td>\n",
       "      <td>Order_kK1V8DEQ</td>\n",
       "      <td>Order_kK1V8DEQ</td>\n",
       "      <td>Trade_3Cq2vZib</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>-3.6225</td>\n",
       "      <td>-21.735</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>2018-01-15 00:00:00</td>\n",
       "      <td>300245</td>\n",
       "      <td>13.38</td>\n",
       "      <td>-1000</td>\n",
       "      <td>35152.0200</td>\n",
       "      <td>Order_qcGuE2ij</td>\n",
       "      <td>Order_qcGuE2ij</td>\n",
       "      <td>Trade_ubTdkr14</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>-3.3450</td>\n",
       "      <td>-20.070</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>2018-01-15 00:00:00</td>\n",
       "      <td>300290</td>\n",
       "      <td>8.08</td>\n",
       "      <td>-1000</td>\n",
       "      <td>43246.1600</td>\n",
       "      <td>Order_XAcLutCp</td>\n",
       "      <td>Order_XAcLutCp</td>\n",
       "      <td>Trade_OjA3lpNn</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>-2.0200</td>\n",
       "      <td>-12.120</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>2018-01-15 00:00:00</td>\n",
       "      <td>600198</td>\n",
       "      <td>10.61</td>\n",
       "      <td>-1000</td>\n",
       "      <td>53874.7275</td>\n",
       "      <td>Order_VXd1B3KE</td>\n",
       "      <td>Order_VXd1B3KE</td>\n",
       "      <td>Trade_KqQpcCGy</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>-2.6525</td>\n",
       "      <td>-15.915</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>2018-01-16 00:00:00</td>\n",
       "      <td>000063</td>\n",
       "      <td>38.60</td>\n",
       "      <td>1000</td>\n",
       "      <td>15207.1775</td>\n",
       "      <td>Order_xfhHbnI0</td>\n",
       "      <td>Order_xfhHbnI0</td>\n",
       "      <td>Trade_2ctPwXGN</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>9.6500</td>\n",
       "      <td>57.900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>2018-01-16 00:00:00</td>\n",
       "      <td>002544</td>\n",
       "      <td>14.62</td>\n",
       "      <td>-1000</td>\n",
       "      <td>29852.7625</td>\n",
       "      <td>Order_ydeshXSg</td>\n",
       "      <td>Order_ydeshXSg</td>\n",
       "      <td>Trade_JgWf6d1e</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>-3.6550</td>\n",
       "      <td>-21.930</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>2018-01-16 00:00:00</td>\n",
       "      <td>600718</td>\n",
       "      <td>14.27</td>\n",
       "      <td>-1000</td>\n",
       "      <td>44147.7350</td>\n",
       "      <td>Order_tWCmXwzc</td>\n",
       "      <td>Order_tWCmXwzc</td>\n",
       "      <td>Trade_0jDlCpSA</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>-3.5675</td>\n",
       "      <td>-21.405</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>2018-01-16 00:00:00</td>\n",
       "      <td>600804</td>\n",
       "      <td>16.51</td>\n",
       "      <td>-1000</td>\n",
       "      <td>60686.6275</td>\n",
       "      <td>Order_tZncUvNb</td>\n",
       "      <td>Order_tZncUvNb</td>\n",
       "      <td>Trade_ChUqo3HI</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>-4.1275</td>\n",
       "      <td>-24.765</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>2018-01-17 00:00:00</td>\n",
       "      <td>300297</td>\n",
       "      <td>9.56</td>\n",
       "      <td>1000</td>\n",
       "      <td>51109.8975</td>\n",
       "      <td>Order_X3FLjoUW</td>\n",
       "      <td>Order_X3FLjoUW</td>\n",
       "      <td>Trade_qtGE2dYw</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>2.3900</td>\n",
       "      <td>14.340</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>2018-01-19 00:00:00</td>\n",
       "      <td>000063</td>\n",
       "      <td>36.86</td>\n",
       "      <td>-1000</td>\n",
       "      <td>88034.4025</td>\n",
       "      <td>Order_gwUSRf3G</td>\n",
       "      <td>Order_gwUSRf3G</td>\n",
       "      <td>Trade_jTevtxld</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>-9.2150</td>\n",
       "      <td>-55.290</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>2018-01-19 00:00:00</td>\n",
       "      <td>002279</td>\n",
       "      <td>10.33</td>\n",
       "      <td>1000</td>\n",
       "      <td>77686.3250</td>\n",
       "      <td>Order_nuivkPTW</td>\n",
       "      <td>Order_nuivkPTW</td>\n",
       "      <td>Trade_PKRkTfIc</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>2.5825</td>\n",
       "      <td>15.495</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>104</th>\n",
       "      <td>2018-04-12 00:00:00</td>\n",
       "      <td>600198</td>\n",
       "      <td>8.32</td>\n",
       "      <td>1000</td>\n",
       "      <td>421.3475</td>\n",
       "      <td>Order_pjNsHFm5</td>\n",
       "      <td>Order_pjNsHFm5</td>\n",
       "      <td>Trade_KdhnNHOe</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>2.0800</td>\n",
       "      <td>12.480</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>105</th>\n",
       "      <td>2018-04-13 00:00:00</td>\n",
       "      <td>300085</td>\n",
       "      <td>16.34</td>\n",
       "      <td>-1000</td>\n",
       "      <td>16789.9425</td>\n",
       "      <td>Order_g3w6Eir7</td>\n",
       "      <td>Order_g3w6Eir7</td>\n",
       "      <td>Trade_j2tT6B3x</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>-4.0850</td>\n",
       "      <td>-24.510</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>106</th>\n",
       "      <td>2018-04-13 00:00:00</td>\n",
       "      <td>300287</td>\n",
       "      <td>9.80</td>\n",
       "      <td>1000</td>\n",
       "      <td>6972.7925</td>\n",
       "      <td>Order_vi4usBEU</td>\n",
       "      <td>Order_vi4usBEU</td>\n",
       "      <td>Trade_8NPLyuqB</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>2.4500</td>\n",
       "      <td>14.700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>107</th>\n",
       "      <td>2018-04-13 00:00:00</td>\n",
       "      <td>300383</td>\n",
       "      <td>17.75</td>\n",
       "      <td>-1000</td>\n",
       "      <td>24753.8550</td>\n",
       "      <td>Order_avKOAeWI</td>\n",
       "      <td>Order_avKOAeWI</td>\n",
       "      <td>Trade_UvTz98l6</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>-4.4375</td>\n",
       "      <td>-26.625</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>108</th>\n",
       "      <td>2018-04-13 00:00:00</td>\n",
       "      <td>600589</td>\n",
       "      <td>5.47</td>\n",
       "      <td>1000</td>\n",
       "      <td>19274.2825</td>\n",
       "      <td>Order_kLGItRjr</td>\n",
       "      <td>Order_kLGItRjr</td>\n",
       "      <td>Trade_XwPiIrMC</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>1.3675</td>\n",
       "      <td>8.205</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>109</th>\n",
       "      <td>2018-04-13 00:00:00</td>\n",
       "      <td>600590</td>\n",
       "      <td>12.11</td>\n",
       "      <td>1000</td>\n",
       "      <td>7143.0900</td>\n",
       "      <td>Order_E2Vx6M3o</td>\n",
       "      <td>Order_E2Vx6M3o</td>\n",
       "      <td>Trade_IuTMkVep</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>3.0275</td>\n",
       "      <td>18.165</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110</th>\n",
       "      <td>2018-04-13 00:00:00</td>\n",
       "      <td>601928</td>\n",
       "      <td>7.27</td>\n",
       "      <td>-1000</td>\n",
       "      <td>14425.8125</td>\n",
       "      <td>Order_XLp31JS6</td>\n",
       "      <td>Order_XLp31JS6</td>\n",
       "      <td>Trade_R87jVyex</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>-1.8175</td>\n",
       "      <td>-10.905</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>111</th>\n",
       "      <td>2018-04-16 00:00:00</td>\n",
       "      <td>002065</td>\n",
       "      <td>8.40</td>\n",
       "      <td>1000</td>\n",
       "      <td>6011.1125</td>\n",
       "      <td>Order_ubHjJ3Tr</td>\n",
       "      <td>Order_ubHjJ3Tr</td>\n",
       "      <td>Trade_jTY5sS7D</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>2.1000</td>\n",
       "      <td>12.600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>112</th>\n",
       "      <td>2018-04-17 00:00:00</td>\n",
       "      <td>300287</td>\n",
       "      <td>9.56</td>\n",
       "      <td>-1000</td>\n",
       "      <td>15587.8425</td>\n",
       "      <td>Order_myObDLoh</td>\n",
       "      <td>Order_myObDLoh</td>\n",
       "      <td>Trade_ds7iXu4V</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>-2.3900</td>\n",
       "      <td>-14.340</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113</th>\n",
       "      <td>2018-04-17 00:00:00</td>\n",
       "      <td>600589</td>\n",
       "      <td>5.37</td>\n",
       "      <td>-1000</td>\n",
       "      <td>20967.2400</td>\n",
       "      <td>Order_fzOQt846</td>\n",
       "      <td>Order_fzOQt846</td>\n",
       "      <td>Trade_DQlIEonw</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>-1.3425</td>\n",
       "      <td>-8.055</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>114</th>\n",
       "      <td>2018-04-17 00:00:00</td>\n",
       "      <td>600770</td>\n",
       "      <td>7.12</td>\n",
       "      <td>-1000</td>\n",
       "      <td>28099.7000</td>\n",
       "      <td>Order_Ae5XduIP</td>\n",
       "      <td>Order_Ae5XduIP</td>\n",
       "      <td>Trade_amJjUL0o</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>-1.7800</td>\n",
       "      <td>-10.680</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>115</th>\n",
       "      <td>2018-04-18 00:00:00</td>\n",
       "      <td>002463</td>\n",
       "      <td>4.35</td>\n",
       "      <td>1000</td>\n",
       "      <td>23742.0875</td>\n",
       "      <td>Order_X7xe5kOH</td>\n",
       "      <td>Order_X7xe5kOH</td>\n",
       "      <td>Trade_TVimMICX</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>1.0875</td>\n",
       "      <td>6.525</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>116</th>\n",
       "      <td>2018-04-18 00:00:00</td>\n",
       "      <td>300051</td>\n",
       "      <td>12.00</td>\n",
       "      <td>1000</td>\n",
       "      <td>11721.0875</td>\n",
       "      <td>Order_pcYyubnM</td>\n",
       "      <td>Order_pcYyubnM</td>\n",
       "      <td>Trade_R1KrCWaw</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>3.0000</td>\n",
       "      <td>18.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>117</th>\n",
       "      <td>2018-04-18 00:00:00</td>\n",
       "      <td>600100</td>\n",
       "      <td>10.74</td>\n",
       "      <td>1000</td>\n",
       "      <td>962.2925</td>\n",
       "      <td>Order_fR1zVgNU</td>\n",
       "      <td>Order_fR1zVgNU</td>\n",
       "      <td>Trade_cj2bPWtZ</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>2.6850</td>\n",
       "      <td>16.110</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>118</th>\n",
       "      <td>2018-04-20 00:00:00</td>\n",
       "      <td>300051</td>\n",
       "      <td>11.29</td>\n",
       "      <td>-1000</td>\n",
       "      <td>12272.0500</td>\n",
       "      <td>Order_7g6uwcl4</td>\n",
       "      <td>Order_7g6uwcl4</td>\n",
       "      <td>Trade_OaPhtvDf</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>-2.8225</td>\n",
       "      <td>-16.935</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>119</th>\n",
       "      <td>2018-04-20 00:00:00</td>\n",
       "      <td>600589</td>\n",
       "      <td>5.47</td>\n",
       "      <td>1000</td>\n",
       "      <td>6792.4775</td>\n",
       "      <td>Order_p5UcQmBw</td>\n",
       "      <td>Order_p5UcQmBw</td>\n",
       "      <td>Trade_6fkmJV4P</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>1.3675</td>\n",
       "      <td>8.205</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>120</th>\n",
       "      <td>2018-04-20 00:00:00</td>\n",
       "      <td>600590</td>\n",
       "      <td>11.29</td>\n",
       "      <td>-1000</td>\n",
       "      <td>18102.2350</td>\n",
       "      <td>Order_img5TnKy</td>\n",
       "      <td>Order_img5TnKy</td>\n",
       "      <td>Trade_fjUkgyIM</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>-2.8225</td>\n",
       "      <td>-16.935</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>121</th>\n",
       "      <td>2018-04-20 00:00:00</td>\n",
       "      <td>600601</td>\n",
       "      <td>3.09</td>\n",
       "      <td>1000</td>\n",
       "      <td>15006.8275</td>\n",
       "      <td>Order_dI9SJy3q</td>\n",
       "      <td>Order_dI9SJy3q</td>\n",
       "      <td>Trade_S7k6KvgN</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>0.7725</td>\n",
       "      <td>4.635</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>122</th>\n",
       "      <td>2018-04-23 00:00:00</td>\n",
       "      <td>300366</td>\n",
       "      <td>12.45</td>\n",
       "      <td>1000</td>\n",
       "      <td>2535.0400</td>\n",
       "      <td>Order_k2rIMafR</td>\n",
       "      <td>Order_k2rIMafR</td>\n",
       "      <td>Trade_NVH6ZrhU</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>3.1125</td>\n",
       "      <td>18.675</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>123</th>\n",
       "      <td>2018-04-23 00:00:00</td>\n",
       "      <td>600601</td>\n",
       "      <td>3.08</td>\n",
       "      <td>-1000</td>\n",
       "      <td>5620.4300</td>\n",
       "      <td>Order_dtTBM43Y</td>\n",
       "      <td>Order_dtTBM43Y</td>\n",
       "      <td>Trade_VchbZSEH</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>-0.7700</td>\n",
       "      <td>-4.620</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>124</th>\n",
       "      <td>2018-04-24 00:00:00</td>\n",
       "      <td>600601</td>\n",
       "      <td>3.08</td>\n",
       "      <td>1000</td>\n",
       "      <td>2535.0400</td>\n",
       "      <td>Order_xrFNEVC4</td>\n",
       "      <td>Order_xrFNEVC4</td>\n",
       "      <td>Trade_BlUXpNAc</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>0.7700</td>\n",
       "      <td>4.620</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>125</th>\n",
       "      <td>2018-04-25 00:00:00</td>\n",
       "      <td>600845</td>\n",
       "      <td>30.00</td>\n",
       "      <td>-1000</td>\n",
       "      <td>32587.5400</td>\n",
       "      <td>Order_qm1vYekP</td>\n",
       "      <td>Order_qm1vYekP</td>\n",
       "      <td>Trade_Z8PMI0wO</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>-7.5000</td>\n",
       "      <td>-45.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>126</th>\n",
       "      <td>2018-04-26 00:00:00</td>\n",
       "      <td>000066</td>\n",
       "      <td>9.28</td>\n",
       "      <td>-1000</td>\n",
       "      <td>41883.7800</td>\n",
       "      <td>Order_Q5H2Fkrm</td>\n",
       "      <td>Order_Q5H2Fkrm</td>\n",
       "      <td>Trade_5kSnPrJ0</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>-2.3200</td>\n",
       "      <td>-13.920</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>127</th>\n",
       "      <td>2018-04-26 00:00:00</td>\n",
       "      <td>000611</td>\n",
       "      <td>7.56</td>\n",
       "      <td>1000</td>\n",
       "      <td>34310.5500</td>\n",
       "      <td>Order_5vLmotrf</td>\n",
       "      <td>Order_5vLmotrf</td>\n",
       "      <td>Trade_9aXfk1ur</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>1.8900</td>\n",
       "      <td>11.340</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>128</th>\n",
       "      <td>2018-04-26 00:00:00</td>\n",
       "      <td>000836</td>\n",
       "      <td>4.56</td>\n",
       "      <td>1000</td>\n",
       "      <td>29742.5700</td>\n",
       "      <td>Order_8c0vIeK3</td>\n",
       "      <td>Order_8c0vIeK3</td>\n",
       "      <td>Trade_aez4PKrt</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>1.1400</td>\n",
       "      <td>6.840</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>129</th>\n",
       "      <td>2018-04-26 00:00:00</td>\n",
       "      <td>002063</td>\n",
       "      <td>11.72</td>\n",
       "      <td>1000</td>\n",
       "      <td>18002.0600</td>\n",
       "      <td>Order_v26iRnZQ</td>\n",
       "      <td>Order_v26iRnZQ</td>\n",
       "      <td>Trade_CtKujRbr</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>2.9300</td>\n",
       "      <td>17.580</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>130</th>\n",
       "      <td>2018-04-26 00:00:00</td>\n",
       "      <td>300025</td>\n",
       "      <td>5.07</td>\n",
       "      <td>1000</td>\n",
       "      <td>12923.1875</td>\n",
       "      <td>Order_U1mKR6OG</td>\n",
       "      <td>Order_U1mKR6OG</td>\n",
       "      <td>Trade_18JMpRnG</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>1.2675</td>\n",
       "      <td>7.605</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>131</th>\n",
       "      <td>2018-04-26 00:00:00</td>\n",
       "      <td>300235</td>\n",
       "      <td>12.37</td>\n",
       "      <td>1000</td>\n",
       "      <td>531.5400</td>\n",
       "      <td>Order_8HUWfJx1</td>\n",
       "      <td>Order_8HUWfJx1</td>\n",
       "      <td>Trade_WPNlvA1E</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>3.0925</td>\n",
       "      <td>18.555</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>132</th>\n",
       "      <td>2018-04-27 00:00:00</td>\n",
       "      <td>002063</td>\n",
       "      <td>11.64</td>\n",
       "      <td>-1000</td>\n",
       "      <td>12191.9100</td>\n",
       "      <td>Order_BtPZvUWw</td>\n",
       "      <td>Order_BtPZvUWw</td>\n",
       "      <td>Trade_ICkVoQOZ</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>-2.9100</td>\n",
       "      <td>-17.460</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>133</th>\n",
       "      <td>2018-04-27 00:00:00</td>\n",
       "      <td>601360</td>\n",
       "      <td>37.80</td>\n",
       "      <td>-1000</td>\n",
       "      <td>50058.0600</td>\n",
       "      <td>Order_lyDrw7iT</td>\n",
       "      <td>Order_lyDrw7iT</td>\n",
       "      <td>Trade_3aozRWnk</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>-9.4500</td>\n",
       "      <td>-56.700</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>134 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                datetime    code  price  amount         cash        order_id  \\\n",
       "0    2018-01-02 00:00:00  002195   5.91    1000  194079.6575  Order_AGZefuXd   \n",
       "1    2018-01-02 00:00:00  002456  20.78    1000  173263.2925  Order_qOuEB4fo   \n",
       "2    2018-01-02 00:00:00  002544  15.85    1000  157385.5550  Order_ripYwt6L   \n",
       "3    2018-01-02 00:00:00  300290   8.71    1000  148660.3125  Order_ph50Tje9   \n",
       "4    2018-01-02 00:00:00  300367  15.39    1000  133243.3800  Order_YvlByWfD   \n",
       "5    2018-01-02 00:00:00  600105   6.58    1000  126651.8650  Order_8sBTIvLO   \n",
       "6    2018-01-02 00:00:00  600797  11.87    1000  114761.0925  Order_whQIWHBi   \n",
       "7    2018-01-03 00:00:00  000070   9.52    1000  105224.4325  Order_wDPTJiRh   \n",
       "8    2018-01-03 00:00:00  000100   3.99    1000  101227.4500  Order_f8yNTPHe   \n",
       "9    2018-01-03 00:00:00  002065   8.53    1000   92682.5225  Order_x5k8PvbA   \n",
       "10   2018-01-03 00:00:00  002335  30.04    1000   62589.9525  Order_jKYkEcmX   \n",
       "11   2018-01-03 00:00:00  300036  15.78    1000   46782.3375  Order_iB3KzEPv   \n",
       "12   2018-01-03 00:00:00  600198  11.65    1000   35111.9500  Order_eFZH05bs   \n",
       "13   2018-01-03 00:00:00  600718  15.00    1000   20085.7000  Order_K3MjyXZo   \n",
       "14   2018-01-03 00:00:00  600804  17.93    1000    2124.3225  Order_EdD6u1Cb   \n",
       "15   2018-01-09 00:00:00  300367  14.91   -1000   17060.4150  Order_KYdA3NQ9   \n",
       "16   2018-01-10 00:00:00  300245  13.80    1000    3236.2650  Order_uCE5pWke   \n",
       "17   2018-01-12 00:00:00  002456  19.84   -1000   23110.9850  Order_p5J1Paxo   \n",
       "18   2018-01-12 00:00:00  300052  15.85    1000    7233.2475  Order_GOfSMKya   \n",
       "19   2018-01-15 00:00:00  300036  14.49   -1000   21748.6050  Order_kK1V8DEQ   \n",
       "20   2018-01-15 00:00:00  300245  13.38   -1000   35152.0200  Order_qcGuE2ij   \n",
       "21   2018-01-15 00:00:00  300290   8.08   -1000   43246.1600  Order_XAcLutCp   \n",
       "22   2018-01-15 00:00:00  600198  10.61   -1000   53874.7275  Order_VXd1B3KE   \n",
       "23   2018-01-16 00:00:00  000063  38.60    1000   15207.1775  Order_xfhHbnI0   \n",
       "24   2018-01-16 00:00:00  002544  14.62   -1000   29852.7625  Order_ydeshXSg   \n",
       "25   2018-01-16 00:00:00  600718  14.27   -1000   44147.7350  Order_tWCmXwzc   \n",
       "26   2018-01-16 00:00:00  600804  16.51   -1000   60686.6275  Order_tZncUvNb   \n",
       "27   2018-01-17 00:00:00  300297   9.56    1000   51109.8975  Order_X3FLjoUW   \n",
       "28   2018-01-19 00:00:00  000063  36.86   -1000   88034.4025  Order_gwUSRf3G   \n",
       "29   2018-01-19 00:00:00  002279  10.33    1000   77686.3250  Order_nuivkPTW   \n",
       "..                   ...     ...    ...     ...          ...             ...   \n",
       "104  2018-04-12 00:00:00  600198   8.32    1000     421.3475  Order_pjNsHFm5   \n",
       "105  2018-04-13 00:00:00  300085  16.34   -1000   16789.9425  Order_g3w6Eir7   \n",
       "106  2018-04-13 00:00:00  300287   9.80    1000    6972.7925  Order_vi4usBEU   \n",
       "107  2018-04-13 00:00:00  300383  17.75   -1000   24753.8550  Order_avKOAeWI   \n",
       "108  2018-04-13 00:00:00  600589   5.47    1000   19274.2825  Order_kLGItRjr   \n",
       "109  2018-04-13 00:00:00  600590  12.11    1000    7143.0900  Order_E2Vx6M3o   \n",
       "110  2018-04-13 00:00:00  601928   7.27   -1000   14425.8125  Order_XLp31JS6   \n",
       "111  2018-04-16 00:00:00  002065   8.40    1000    6011.1125  Order_ubHjJ3Tr   \n",
       "112  2018-04-17 00:00:00  300287   9.56   -1000   15587.8425  Order_myObDLoh   \n",
       "113  2018-04-17 00:00:00  600589   5.37   -1000   20967.2400  Order_fzOQt846   \n",
       "114  2018-04-17 00:00:00  600770   7.12   -1000   28099.7000  Order_Ae5XduIP   \n",
       "115  2018-04-18 00:00:00  002463   4.35    1000   23742.0875  Order_X7xe5kOH   \n",
       "116  2018-04-18 00:00:00  300051  12.00    1000   11721.0875  Order_pcYyubnM   \n",
       "117  2018-04-18 00:00:00  600100  10.74    1000     962.2925  Order_fR1zVgNU   \n",
       "118  2018-04-20 00:00:00  300051  11.29   -1000   12272.0500  Order_7g6uwcl4   \n",
       "119  2018-04-20 00:00:00  600589   5.47    1000    6792.4775  Order_p5UcQmBw   \n",
       "120  2018-04-20 00:00:00  600590  11.29   -1000   18102.2350  Order_img5TnKy   \n",
       "121  2018-04-20 00:00:00  600601   3.09    1000   15006.8275  Order_dI9SJy3q   \n",
       "122  2018-04-23 00:00:00  300366  12.45    1000    2535.0400  Order_k2rIMafR   \n",
       "123  2018-04-23 00:00:00  600601   3.08   -1000    5620.4300  Order_dtTBM43Y   \n",
       "124  2018-04-24 00:00:00  600601   3.08    1000    2535.0400  Order_xrFNEVC4   \n",
       "125  2018-04-25 00:00:00  600845  30.00   -1000   32587.5400  Order_qm1vYekP   \n",
       "126  2018-04-26 00:00:00  000066   9.28   -1000   41883.7800  Order_Q5H2Fkrm   \n",
       "127  2018-04-26 00:00:00  000611   7.56    1000   34310.5500  Order_5vLmotrf   \n",
       "128  2018-04-26 00:00:00  000836   4.56    1000   29742.5700  Order_8c0vIeK3   \n",
       "129  2018-04-26 00:00:00  002063  11.72    1000   18002.0600  Order_v26iRnZQ   \n",
       "130  2018-04-26 00:00:00  300025   5.07    1000   12923.1875  Order_U1mKR6OG   \n",
       "131  2018-04-26 00:00:00  300235  12.37    1000     531.5400  Order_8HUWfJx1   \n",
       "132  2018-04-27 00:00:00  002063  11.64   -1000   12191.9100  Order_BtPZvUWw   \n",
       "133  2018-04-27 00:00:00  601360  37.80   -1000   50058.0600  Order_lyDrw7iT   \n",
       "\n",
       "       realorder_id        trade_id account_cookie  commission     tax  \n",
       "0    Order_AGZefuXd  Trade_7RxnPTq1   JCSC_EXAMPLE      1.4775   8.865  \n",
       "1    Order_qOuEB4fo  Trade_5IZEW2LB   JCSC_EXAMPLE      5.1950  31.170  \n",
       "2    Order_ripYwt6L  Trade_VzvpFjPM   JCSC_EXAMPLE      3.9625  23.775  \n",
       "3    Order_ph50Tje9  Trade_vWYaMmhq   JCSC_EXAMPLE      2.1775  13.065  \n",
       "4    Order_YvlByWfD  Trade_zWlyg0UM   JCSC_EXAMPLE      3.8475  23.085  \n",
       "5    Order_8sBTIvLO  Trade_cay7rZ6J   JCSC_EXAMPLE      1.6450   9.870  \n",
       "6    Order_whQIWHBi  Trade_NtWVGFSo   JCSC_EXAMPLE      2.9675  17.805  \n",
       "7    Order_wDPTJiRh  Trade_eufovKcX   JCSC_EXAMPLE      2.3800  14.280  \n",
       "8    Order_f8yNTPHe  Trade_OUEDoFnu   JCSC_EXAMPLE      0.9975   5.985  \n",
       "9    Order_x5k8PvbA  Trade_dBbge5v4   JCSC_EXAMPLE      2.1325  12.795  \n",
       "10   Order_jKYkEcmX  Trade_L1dMti6K   JCSC_EXAMPLE      7.5100  45.060  \n",
       "11   Order_iB3KzEPv  Trade_rXCb1PJu   JCSC_EXAMPLE      3.9450  23.670  \n",
       "12   Order_eFZH05bs  Trade_nHqFwT30   JCSC_EXAMPLE      2.9125  17.475  \n",
       "13   Order_K3MjyXZo  Trade_zrGbK97E   JCSC_EXAMPLE      3.7500  22.500  \n",
       "14   Order_EdD6u1Cb  Trade_Bw0n39H5   JCSC_EXAMPLE      4.4825  26.895  \n",
       "15   Order_KYdA3NQ9  Trade_rf1oEbiF   JCSC_EXAMPLE     -3.7275 -22.365  \n",
       "16   Order_uCE5pWke  Trade_ZGCEmfb8   JCSC_EXAMPLE      3.4500  20.700  \n",
       "17   Order_p5J1Paxo  Trade_1quYOxnZ   JCSC_EXAMPLE     -4.9600 -29.760  \n",
       "18   Order_GOfSMKya  Trade_PIZ23WAV   JCSC_EXAMPLE      3.9625  23.775  \n",
       "19   Order_kK1V8DEQ  Trade_3Cq2vZib   JCSC_EXAMPLE     -3.6225 -21.735  \n",
       "20   Order_qcGuE2ij  Trade_ubTdkr14   JCSC_EXAMPLE     -3.3450 -20.070  \n",
       "21   Order_XAcLutCp  Trade_OjA3lpNn   JCSC_EXAMPLE     -2.0200 -12.120  \n",
       "22   Order_VXd1B3KE  Trade_KqQpcCGy   JCSC_EXAMPLE     -2.6525 -15.915  \n",
       "23   Order_xfhHbnI0  Trade_2ctPwXGN   JCSC_EXAMPLE      9.6500  57.900  \n",
       "24   Order_ydeshXSg  Trade_JgWf6d1e   JCSC_EXAMPLE     -3.6550 -21.930  \n",
       "25   Order_tWCmXwzc  Trade_0jDlCpSA   JCSC_EXAMPLE     -3.5675 -21.405  \n",
       "26   Order_tZncUvNb  Trade_ChUqo3HI   JCSC_EXAMPLE     -4.1275 -24.765  \n",
       "27   Order_X3FLjoUW  Trade_qtGE2dYw   JCSC_EXAMPLE      2.3900  14.340  \n",
       "28   Order_gwUSRf3G  Trade_jTevtxld   JCSC_EXAMPLE     -9.2150 -55.290  \n",
       "29   Order_nuivkPTW  Trade_PKRkTfIc   JCSC_EXAMPLE      2.5825  15.495  \n",
       "..              ...             ...            ...         ...     ...  \n",
       "104  Order_pjNsHFm5  Trade_KdhnNHOe   JCSC_EXAMPLE      2.0800  12.480  \n",
       "105  Order_g3w6Eir7  Trade_j2tT6B3x   JCSC_EXAMPLE     -4.0850 -24.510  \n",
       "106  Order_vi4usBEU  Trade_8NPLyuqB   JCSC_EXAMPLE      2.4500  14.700  \n",
       "107  Order_avKOAeWI  Trade_UvTz98l6   JCSC_EXAMPLE     -4.4375 -26.625  \n",
       "108  Order_kLGItRjr  Trade_XwPiIrMC   JCSC_EXAMPLE      1.3675   8.205  \n",
       "109  Order_E2Vx6M3o  Trade_IuTMkVep   JCSC_EXAMPLE      3.0275  18.165  \n",
       "110  Order_XLp31JS6  Trade_R87jVyex   JCSC_EXAMPLE     -1.8175 -10.905  \n",
       "111  Order_ubHjJ3Tr  Trade_jTY5sS7D   JCSC_EXAMPLE      2.1000  12.600  \n",
       "112  Order_myObDLoh  Trade_ds7iXu4V   JCSC_EXAMPLE     -2.3900 -14.340  \n",
       "113  Order_fzOQt846  Trade_DQlIEonw   JCSC_EXAMPLE     -1.3425  -8.055  \n",
       "114  Order_Ae5XduIP  Trade_amJjUL0o   JCSC_EXAMPLE     -1.7800 -10.680  \n",
       "115  Order_X7xe5kOH  Trade_TVimMICX   JCSC_EXAMPLE      1.0875   6.525  \n",
       "116  Order_pcYyubnM  Trade_R1KrCWaw   JCSC_EXAMPLE      3.0000  18.000  \n",
       "117  Order_fR1zVgNU  Trade_cj2bPWtZ   JCSC_EXAMPLE      2.6850  16.110  \n",
       "118  Order_7g6uwcl4  Trade_OaPhtvDf   JCSC_EXAMPLE     -2.8225 -16.935  \n",
       "119  Order_p5UcQmBw  Trade_6fkmJV4P   JCSC_EXAMPLE      1.3675   8.205  \n",
       "120  Order_img5TnKy  Trade_fjUkgyIM   JCSC_EXAMPLE     -2.8225 -16.935  \n",
       "121  Order_dI9SJy3q  Trade_S7k6KvgN   JCSC_EXAMPLE      0.7725   4.635  \n",
       "122  Order_k2rIMafR  Trade_NVH6ZrhU   JCSC_EXAMPLE      3.1125  18.675  \n",
       "123  Order_dtTBM43Y  Trade_VchbZSEH   JCSC_EXAMPLE     -0.7700  -4.620  \n",
       "124  Order_xrFNEVC4  Trade_BlUXpNAc   JCSC_EXAMPLE      0.7700   4.620  \n",
       "125  Order_qm1vYekP  Trade_Z8PMI0wO   JCSC_EXAMPLE     -7.5000 -45.000  \n",
       "126  Order_Q5H2Fkrm  Trade_5kSnPrJ0   JCSC_EXAMPLE     -2.3200 -13.920  \n",
       "127  Order_5vLmotrf  Trade_9aXfk1ur   JCSC_EXAMPLE      1.8900  11.340  \n",
       "128  Order_8c0vIeK3  Trade_aez4PKrt   JCSC_EXAMPLE      1.1400   6.840  \n",
       "129  Order_v26iRnZQ  Trade_CtKujRbr   JCSC_EXAMPLE      2.9300  17.580  \n",
       "130  Order_U1mKR6OG  Trade_18JMpRnG   JCSC_EXAMPLE      1.2675   7.605  \n",
       "131  Order_8HUWfJx1  Trade_WPNlvA1E   JCSC_EXAMPLE      3.0925  18.555  \n",
       "132  Order_BtPZvUWw  Trade_ICkVoQOZ   JCSC_EXAMPLE     -2.9100 -17.460  \n",
       "133  Order_lyDrw7iT  Trade_3aozRWnk   JCSC_EXAMPLE     -9.4500 -56.700  \n",
       "\n",
       "[134 rows x 11 columns]"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Account.history_table"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>code</th>\n",
       "      <th>000063</th>\n",
       "      <th>000066</th>\n",
       "      <th>000070</th>\n",
       "      <th>000100</th>\n",
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       "      <th>600770</th>\n",
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       "      <th>601360</th>\n",
       "      <th>601928</th>\n",
       "      <th>603138</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th>account_cookie</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "    </tr>\n",
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       "  <tbody>\n",
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       "      <th>2018-01-02</th>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
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       "      <th>2018-01-09</th>\n",
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       "      <td>1000.0</td>\n",
       "      <td>1000.0</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-12</th>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-15</th>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-16</th>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-17</th>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-19</th>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-22</th>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-23</th>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-24</th>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-25</th>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-29</th>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-31</th>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-02-01</th>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-02-02</th>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-02-06</th>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-02-07</th>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-02-08</th>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-02-12</th>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-02-22</th>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-03-02</th>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-03-07</th>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-03-09</th>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-03-12</th>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-03-14</th>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-03-16</th>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-03-19</th>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-03-20</th>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-03-21</th>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-03-22</th>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-03-23</th>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-03-26</th>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-03-27</th>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-04-04</th>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-04-09</th>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-04-10</th>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-04-11</th>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-04-12</th>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-04-13</th>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-04-16</th>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-04-17</th>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-04-18</th>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-04-20</th>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-04-23</th>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-04-24</th>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-04-25</th>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-04-26</th>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-04-27</th>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>50 rows × 56 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "code                       000063  000066  000070  000100  000611  000836  \\\n",
       "date       account_cookie                                                   \n",
       "2018-01-02 JCSC_EXAMPLE       0.0     0.0     0.0     0.0     0.0     0.0   \n",
       "2018-01-03 JCSC_EXAMPLE       0.0     0.0  1000.0  1000.0     0.0     0.0   \n",
       "2018-01-09 JCSC_EXAMPLE       0.0     0.0  1000.0  1000.0     0.0     0.0   \n",
       "2018-01-10 JCSC_EXAMPLE       0.0     0.0  1000.0  1000.0     0.0     0.0   \n",
       "2018-01-12 JCSC_EXAMPLE       0.0     0.0  1000.0  1000.0     0.0     0.0   \n",
       "2018-01-15 JCSC_EXAMPLE       0.0     0.0  1000.0  1000.0     0.0     0.0   \n",
       "2018-01-16 JCSC_EXAMPLE    1000.0     0.0  1000.0  1000.0     0.0     0.0   \n",
       "2018-01-17 JCSC_EXAMPLE    1000.0     0.0  1000.0  1000.0     0.0     0.0   \n",
       "2018-01-19 JCSC_EXAMPLE       0.0     0.0  1000.0  1000.0     0.0     0.0   \n",
       "2018-01-22 JCSC_EXAMPLE       0.0     0.0  1000.0  1000.0     0.0     0.0   \n",
       "2018-01-23 JCSC_EXAMPLE       0.0     0.0  1000.0     0.0     0.0     0.0   \n",
       "2018-01-24 JCSC_EXAMPLE       0.0  1000.0  1000.0     0.0     0.0  1000.0   \n",
       "2018-01-25 JCSC_EXAMPLE       0.0  1000.0  1000.0     0.0     0.0  1000.0   \n",
       "2018-01-29 JCSC_EXAMPLE       0.0  1000.0  1000.0     0.0     0.0  1000.0   \n",
       "2018-01-31 JCSC_EXAMPLE       0.0  1000.0     0.0     0.0     0.0  1000.0   \n",
       "2018-02-01 JCSC_EXAMPLE       0.0     0.0     0.0     0.0     0.0  1000.0   \n",
       "2018-02-02 JCSC_EXAMPLE       0.0     0.0     0.0     0.0     0.0  1000.0   \n",
       "2018-02-06 JCSC_EXAMPLE       0.0     0.0     0.0     0.0     0.0     0.0   \n",
       "2018-02-07 JCSC_EXAMPLE       0.0     0.0     0.0     0.0     0.0     0.0   \n",
       "2018-02-08 JCSC_EXAMPLE       0.0     0.0     0.0     0.0     0.0     0.0   \n",
       "2018-02-12 JCSC_EXAMPLE       0.0     0.0     0.0     0.0     0.0     0.0   \n",
       "2018-02-22 JCSC_EXAMPLE       0.0     0.0     0.0  1000.0     0.0     0.0   \n",
       "2018-03-02 JCSC_EXAMPLE       0.0     0.0     0.0  1000.0     0.0     0.0   \n",
       "2018-03-07 JCSC_EXAMPLE       0.0     0.0     0.0  1000.0     0.0     0.0   \n",
       "2018-03-09 JCSC_EXAMPLE       0.0     0.0     0.0  1000.0     0.0     0.0   \n",
       "2018-03-12 JCSC_EXAMPLE       0.0     0.0     0.0  1000.0     0.0     0.0   \n",
       "2018-03-14 JCSC_EXAMPLE       0.0     0.0     0.0  1000.0     0.0     0.0   \n",
       "2018-03-16 JCSC_EXAMPLE       0.0     0.0     0.0  1000.0     0.0     0.0   \n",
       "2018-03-19 JCSC_EXAMPLE       0.0     0.0     0.0  1000.0     0.0     0.0   \n",
       "2018-03-20 JCSC_EXAMPLE       0.0     0.0     0.0  1000.0     0.0     0.0   \n",
       "2018-03-21 JCSC_EXAMPLE       0.0     0.0     0.0  1000.0     0.0     0.0   \n",
       "2018-03-22 JCSC_EXAMPLE       0.0     0.0     0.0     0.0     0.0     0.0   \n",
       "2018-03-23 JCSC_EXAMPLE       0.0     0.0     0.0     0.0     0.0     0.0   \n",
       "2018-03-26 JCSC_EXAMPLE       0.0     0.0     0.0     0.0     0.0     0.0   \n",
       "2018-03-27 JCSC_EXAMPLE       0.0  1000.0     0.0     0.0     0.0     0.0   \n",
       "2018-04-04 JCSC_EXAMPLE       0.0  1000.0     0.0     0.0     0.0     0.0   \n",
       "2018-04-09 JCSC_EXAMPLE       0.0  1000.0     0.0     0.0     0.0     0.0   \n",
       "2018-04-10 JCSC_EXAMPLE       0.0  1000.0     0.0     0.0     0.0     0.0   \n",
       "2018-04-11 JCSC_EXAMPLE       0.0  1000.0     0.0     0.0     0.0     0.0   \n",
       "2018-04-12 JCSC_EXAMPLE       0.0  1000.0     0.0     0.0     0.0     0.0   \n",
       "2018-04-13 JCSC_EXAMPLE       0.0  1000.0     0.0     0.0     0.0     0.0   \n",
       "2018-04-16 JCSC_EXAMPLE       0.0  1000.0     0.0     0.0     0.0     0.0   \n",
       "2018-04-17 JCSC_EXAMPLE       0.0  1000.0     0.0     0.0     0.0     0.0   \n",
       "2018-04-18 JCSC_EXAMPLE       0.0  1000.0     0.0     0.0     0.0     0.0   \n",
       "2018-04-20 JCSC_EXAMPLE       0.0  1000.0     0.0     0.0     0.0     0.0   \n",
       "2018-04-23 JCSC_EXAMPLE       0.0  1000.0     0.0     0.0     0.0     0.0   \n",
       "2018-04-24 JCSC_EXAMPLE       0.0  1000.0     0.0     0.0     0.0     0.0   \n",
       "2018-04-25 JCSC_EXAMPLE       0.0  1000.0     0.0     0.0     0.0     0.0   \n",
       "2018-04-26 JCSC_EXAMPLE       0.0     0.0     0.0     0.0  1000.0  1000.0   \n",
       "2018-04-27 JCSC_EXAMPLE       0.0     0.0     0.0     0.0  1000.0  1000.0   \n",
       "\n",
       "code                       000977  002063  002065  002095   ...    600601  \\\n",
       "date       account_cookie                                   ...             \n",
       "2018-01-02 JCSC_EXAMPLE       0.0     0.0     0.0     0.0   ...       0.0   \n",
       "2018-01-03 JCSC_EXAMPLE       0.0     0.0  1000.0     0.0   ...       0.0   \n",
       "2018-01-09 JCSC_EXAMPLE       0.0     0.0  1000.0     0.0   ...       0.0   \n",
       "2018-01-10 JCSC_EXAMPLE       0.0     0.0  1000.0     0.0   ...       0.0   \n",
       "2018-01-12 JCSC_EXAMPLE       0.0     0.0  1000.0     0.0   ...       0.0   \n",
       "2018-01-15 JCSC_EXAMPLE       0.0     0.0  1000.0     0.0   ...       0.0   \n",
       "2018-01-16 JCSC_EXAMPLE       0.0     0.0  1000.0     0.0   ...       0.0   \n",
       "2018-01-17 JCSC_EXAMPLE       0.0     0.0  1000.0     0.0   ...       0.0   \n",
       "2018-01-19 JCSC_EXAMPLE       0.0     0.0  1000.0     0.0   ...       0.0   \n",
       "2018-01-22 JCSC_EXAMPLE       0.0     0.0  1000.0  1000.0   ...       0.0   \n",
       "2018-01-23 JCSC_EXAMPLE       0.0     0.0  1000.0  1000.0   ...       0.0   \n",
       "2018-01-24 JCSC_EXAMPLE       0.0     0.0  1000.0  1000.0   ...       0.0   \n",
       "2018-01-25 JCSC_EXAMPLE       0.0     0.0  1000.0  1000.0   ...       0.0   \n",
       "2018-01-29 JCSC_EXAMPLE       0.0     0.0  1000.0  1000.0   ...       0.0   \n",
       "2018-01-31 JCSC_EXAMPLE       0.0     0.0     0.0  1000.0   ...       0.0   \n",
       "2018-02-01 JCSC_EXAMPLE       0.0     0.0     0.0  1000.0   ...       0.0   \n",
       "2018-02-02 JCSC_EXAMPLE       0.0     0.0     0.0  1000.0   ...       0.0   \n",
       "2018-02-06 JCSC_EXAMPLE       0.0     0.0     0.0     0.0   ...       0.0   \n",
       "2018-02-07 JCSC_EXAMPLE       0.0     0.0     0.0     0.0   ...       0.0   \n",
       "2018-02-08 JCSC_EXAMPLE       0.0     0.0     0.0     0.0   ...       0.0   \n",
       "2018-02-12 JCSC_EXAMPLE    1000.0     0.0     0.0     0.0   ...       0.0   \n",
       "2018-02-22 JCSC_EXAMPLE    1000.0     0.0     0.0     0.0   ...       0.0   \n",
       "2018-03-02 JCSC_EXAMPLE    1000.0     0.0     0.0     0.0   ...       0.0   \n",
       "2018-03-07 JCSC_EXAMPLE    1000.0     0.0     0.0     0.0   ...       0.0   \n",
       "2018-03-09 JCSC_EXAMPLE    1000.0     0.0     0.0     0.0   ...       0.0   \n",
       "2018-03-12 JCSC_EXAMPLE    1000.0     0.0     0.0     0.0   ...       0.0   \n",
       "2018-03-14 JCSC_EXAMPLE    1000.0     0.0     0.0     0.0   ...       0.0   \n",
       "2018-03-16 JCSC_EXAMPLE    1000.0     0.0     0.0     0.0   ...       0.0   \n",
       "2018-03-19 JCSC_EXAMPLE    1000.0     0.0     0.0     0.0   ...       0.0   \n",
       "2018-03-20 JCSC_EXAMPLE    1000.0     0.0     0.0     0.0   ...       0.0   \n",
       "2018-03-21 JCSC_EXAMPLE    1000.0     0.0     0.0     0.0   ...       0.0   \n",
       "2018-03-22 JCSC_EXAMPLE    1000.0     0.0     0.0     0.0   ...       0.0   \n",
       "2018-03-23 JCSC_EXAMPLE       0.0     0.0     0.0     0.0   ...       0.0   \n",
       "2018-03-26 JCSC_EXAMPLE    1000.0     0.0     0.0     0.0   ...       0.0   \n",
       "2018-03-27 JCSC_EXAMPLE    1000.0     0.0     0.0     0.0   ...       0.0   \n",
       "2018-04-04 JCSC_EXAMPLE    1000.0     0.0     0.0     0.0   ...       0.0   \n",
       "2018-04-09 JCSC_EXAMPLE    1000.0     0.0     0.0     0.0   ...       0.0   \n",
       "2018-04-10 JCSC_EXAMPLE       0.0     0.0     0.0     0.0   ...       0.0   \n",
       "2018-04-11 JCSC_EXAMPLE       0.0     0.0     0.0     0.0   ...       0.0   \n",
       "2018-04-12 JCSC_EXAMPLE       0.0     0.0     0.0     0.0   ...       0.0   \n",
       "2018-04-13 JCSC_EXAMPLE       0.0     0.0     0.0     0.0   ...       0.0   \n",
       "2018-04-16 JCSC_EXAMPLE       0.0     0.0  1000.0     0.0   ...       0.0   \n",
       "2018-04-17 JCSC_EXAMPLE       0.0     0.0  1000.0     0.0   ...       0.0   \n",
       "2018-04-18 JCSC_EXAMPLE       0.0     0.0  1000.0     0.0   ...       0.0   \n",
       "2018-04-20 JCSC_EXAMPLE       0.0     0.0  1000.0     0.0   ...    1000.0   \n",
       "2018-04-23 JCSC_EXAMPLE       0.0     0.0  1000.0     0.0   ...       0.0   \n",
       "2018-04-24 JCSC_EXAMPLE       0.0     0.0  1000.0     0.0   ...    1000.0   \n",
       "2018-04-25 JCSC_EXAMPLE       0.0     0.0  1000.0     0.0   ...    1000.0   \n",
       "2018-04-26 JCSC_EXAMPLE       0.0  1000.0  1000.0     0.0   ...    1000.0   \n",
       "2018-04-27 JCSC_EXAMPLE       0.0     0.0  1000.0     0.0   ...    1000.0   \n",
       "\n",
       "code                       600718  600770  600797  600804  600845  600996  \\\n",
       "date       account_cookie                                                   \n",
       "2018-01-02 JCSC_EXAMPLE       0.0     0.0  1000.0     0.0     0.0     0.0   \n",
       "2018-01-03 JCSC_EXAMPLE    1000.0     0.0  1000.0  1000.0     0.0     0.0   \n",
       "2018-01-09 JCSC_EXAMPLE    1000.0     0.0  1000.0  1000.0     0.0     0.0   \n",
       "2018-01-10 JCSC_EXAMPLE    1000.0     0.0  1000.0  1000.0     0.0     0.0   \n",
       "2018-01-12 JCSC_EXAMPLE    1000.0     0.0  1000.0  1000.0     0.0     0.0   \n",
       "2018-01-15 JCSC_EXAMPLE    1000.0     0.0  1000.0  1000.0     0.0     0.0   \n",
       "2018-01-16 JCSC_EXAMPLE       0.0     0.0  1000.0     0.0     0.0     0.0   \n",
       "2018-01-17 JCSC_EXAMPLE       0.0     0.0  1000.0     0.0     0.0     0.0   \n",
       "2018-01-19 JCSC_EXAMPLE       0.0     0.0  1000.0  1000.0     0.0     0.0   \n",
       "2018-01-22 JCSC_EXAMPLE       0.0     0.0  1000.0  1000.0     0.0     0.0   \n",
       "2018-01-23 JCSC_EXAMPLE       0.0     0.0     0.0  1000.0     0.0     0.0   \n",
       "2018-01-24 JCSC_EXAMPLE       0.0     0.0     0.0  1000.0     0.0     0.0   \n",
       "2018-01-25 JCSC_EXAMPLE       0.0     0.0     0.0  1000.0     0.0     0.0   \n",
       "2018-01-29 JCSC_EXAMPLE       0.0     0.0     0.0  1000.0     0.0     0.0   \n",
       "2018-01-31 JCSC_EXAMPLE       0.0     0.0     0.0  1000.0     0.0     0.0   \n",
       "2018-02-01 JCSC_EXAMPLE       0.0     0.0     0.0     0.0     0.0     0.0   \n",
       "2018-02-02 JCSC_EXAMPLE       0.0     0.0     0.0     0.0     0.0     0.0   \n",
       "2018-02-06 JCSC_EXAMPLE       0.0     0.0     0.0     0.0     0.0     0.0   \n",
       "2018-02-07 JCSC_EXAMPLE       0.0     0.0     0.0     0.0     0.0     0.0   \n",
       "2018-02-08 JCSC_EXAMPLE       0.0     0.0     0.0     0.0     0.0     0.0   \n",
       "2018-02-12 JCSC_EXAMPLE       0.0     0.0     0.0     0.0     0.0     0.0   \n",
       "2018-02-22 JCSC_EXAMPLE       0.0     0.0     0.0     0.0     0.0     0.0   \n",
       "2018-03-02 JCSC_EXAMPLE       0.0     0.0     0.0     0.0     0.0     0.0   \n",
       "2018-03-07 JCSC_EXAMPLE       0.0     0.0     0.0     0.0     0.0     0.0   \n",
       "2018-03-09 JCSC_EXAMPLE       0.0     0.0     0.0     0.0     0.0     0.0   \n",
       "2018-03-12 JCSC_EXAMPLE       0.0     0.0     0.0     0.0     0.0     0.0   \n",
       "2018-03-14 JCSC_EXAMPLE       0.0     0.0     0.0     0.0     0.0     0.0   \n",
       "2018-03-16 JCSC_EXAMPLE       0.0     0.0     0.0  1000.0     0.0     0.0   \n",
       "2018-03-19 JCSC_EXAMPLE       0.0     0.0     0.0  1000.0     0.0     0.0   \n",
       "2018-03-20 JCSC_EXAMPLE       0.0     0.0     0.0  1000.0     0.0     0.0   \n",
       "2018-03-21 JCSC_EXAMPLE       0.0     0.0     0.0  1000.0     0.0     0.0   \n",
       "2018-03-22 JCSC_EXAMPLE       0.0     0.0     0.0  1000.0     0.0     0.0   \n",
       "2018-03-23 JCSC_EXAMPLE       0.0     0.0     0.0  1000.0     0.0     0.0   \n",
       "2018-03-26 JCSC_EXAMPLE       0.0     0.0     0.0  1000.0     0.0     0.0   \n",
       "2018-03-27 JCSC_EXAMPLE       0.0     0.0     0.0  1000.0     0.0     0.0   \n",
       "2018-04-04 JCSC_EXAMPLE       0.0     0.0     0.0  1000.0     0.0     0.0   \n",
       "2018-04-09 JCSC_EXAMPLE       0.0     0.0     0.0  1000.0     0.0     0.0   \n",
       "2018-04-10 JCSC_EXAMPLE       0.0     0.0     0.0  1000.0     0.0     0.0   \n",
       "2018-04-11 JCSC_EXAMPLE       0.0  1000.0     0.0  1000.0  1000.0  1000.0   \n",
       "2018-04-12 JCSC_EXAMPLE       0.0  1000.0     0.0  1000.0  1000.0  1000.0   \n",
       "2018-04-13 JCSC_EXAMPLE       0.0  1000.0     0.0  1000.0  1000.0  1000.0   \n",
       "2018-04-16 JCSC_EXAMPLE       0.0  1000.0     0.0  1000.0  1000.0  1000.0   \n",
       "2018-04-17 JCSC_EXAMPLE       0.0     0.0     0.0  1000.0  1000.0  1000.0   \n",
       "2018-04-18 JCSC_EXAMPLE       0.0     0.0     0.0  1000.0  1000.0  1000.0   \n",
       "2018-04-20 JCSC_EXAMPLE       0.0     0.0     0.0  1000.0  1000.0  1000.0   \n",
       "2018-04-23 JCSC_EXAMPLE       0.0     0.0     0.0  1000.0  1000.0  1000.0   \n",
       "2018-04-24 JCSC_EXAMPLE       0.0     0.0     0.0  1000.0  1000.0  1000.0   \n",
       "2018-04-25 JCSC_EXAMPLE       0.0     0.0     0.0  1000.0     0.0  1000.0   \n",
       "2018-04-26 JCSC_EXAMPLE       0.0     0.0     0.0  1000.0     0.0  1000.0   \n",
       "2018-04-27 JCSC_EXAMPLE       0.0     0.0     0.0  1000.0     0.0  1000.0   \n",
       "\n",
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       "\n",
       "[50 rows x 56 columns]"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Account.daily_hold"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "Risk=QA.QA_Risk(Account)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'account_cookie': 'JCSC_EXAMPLE',\n",
       " 'portfolio_cookie': None,\n",
       " 'user_cookie': None,\n",
       " 'annualize_return': -0.16,\n",
       " 'profit': -0.05,\n",
       " 'max_dropback': 0.12,\n",
       " 'time_gap': 77,\n",
       " 'volatility': 0.37,\n",
       " 'benchmark_code': '000300',\n",
       " 'bm_annualizereturn': -0.26,\n",
       " 'bn_profit': -0.07,\n",
       " 'beta': 1.0,\n",
       " 'alpha': 0.1,\n",
       " 'sharpe': -0.57,\n",
       " 'init_cash': '200000.00',\n",
       " 'last_assets': '190028.06',\n",
       " 'total_tax': -224.52,\n",
       " 'total_commission': -37.42,\n",
       " 'profit_money': -9971.94}"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Risk.message"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "code\n",
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       "603138        0.0\n",
       "Name: (2018-04-27 00:00:00, JCSC_EXAMPLE), dtype: float64"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Risk.market_value.diff().iloc[-1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
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       "      <th rowspan=\"7\" valign=\"top\">2018-01-02 00:00:00</th>\n",
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       "      <td>2018-01-02 00:00:00</td>\n",
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       "      <th>JCSC_EXAMPLE</th>\n",
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       "      <td>2018-01-02 00:00:00</td>\n",
       "      <td>2018-01-02</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
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       "      <th>JCSC_EXAMPLE</th>\n",
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       "      <td>2018-01-02 00:00:00</td>\n",
       "      <td>2018-01-02</td>\n",
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       "      <td>JCSC_EXAMPLE</td>\n",
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       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>101227</td>\n",
       "      <td>2018-01-03 00:00:00</td>\n",
       "      <td>2018-01-03</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>92682.5</td>\n",
       "      <td>2018-01-03 00:00:00</td>\n",
       "      <td>2018-01-03</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>62590</td>\n",
       "      <td>2018-01-03 00:00:00</td>\n",
       "      <td>2018-01-03</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
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       "    <tr>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
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       "      <td>2018-01-03 00:00:00</td>\n",
       "      <td>2018-01-03</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
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       "      <th>JCSC_EXAMPLE</th>\n",
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       "      <td>2018-01-03 00:00:00</td>\n",
       "      <td>2018-01-03</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
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       "    <tr>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
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       "      <td>2018-01-03 00:00:00</td>\n",
       "      <td>2018-01-03</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>2124.32</td>\n",
       "      <td>2018-01-03 00:00:00</td>\n",
       "      <td>2018-01-03</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
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       "    <tr>\n",
       "      <th>2018-01-09 00:00:00</th>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>17060.4</td>\n",
       "      <td>2018-01-09 00:00:00</td>\n",
       "      <td>2018-01-09</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
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       "    <tr>\n",
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       "      <th>JCSC_EXAMPLE</th>\n",
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       "      <td>2018-01-10 00:00:00</td>\n",
       "      <td>2018-01-10</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
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       "      <th rowspan=\"2\" valign=\"top\">2018-01-12 00:00:00</th>\n",
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       "      <td>2018-01-12 00:00:00</td>\n",
       "      <td>2018-01-12</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
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       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>7233.25</td>\n",
       "      <td>2018-01-12 00:00:00</td>\n",
       "      <td>2018-01-12</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
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       "      <th rowspan=\"4\" valign=\"top\">2018-01-15 00:00:00</th>\n",
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       "      <td>2018-01-15 00:00:00</td>\n",
       "      <td>2018-01-15</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
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       "      <td>2018-01-15 00:00:00</td>\n",
       "      <td>2018-01-15</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
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       "      <td>43246.2</td>\n",
       "      <td>2018-01-15 00:00:00</td>\n",
       "      <td>2018-01-15</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>53874.7</td>\n",
       "      <td>2018-01-15 00:00:00</td>\n",
       "      <td>2018-01-15</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
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       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">2018-01-16 00:00:00</th>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>15207.2</td>\n",
       "      <td>2018-01-16 00:00:00</td>\n",
       "      <td>2018-01-16</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>29852.8</td>\n",
       "      <td>2018-01-16 00:00:00</td>\n",
       "      <td>2018-01-16</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>44147.7</td>\n",
       "      <td>2018-01-16 00:00:00</td>\n",
       "      <td>2018-01-16</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
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       "      <td>2018-01-16</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
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       "      <th>2018-01-17 00:00:00</th>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>51109.9</td>\n",
       "      <td>2018-01-17 00:00:00</td>\n",
       "      <td>2018-01-17</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
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       "      <th rowspan=\"2\" valign=\"top\">2018-01-19 00:00:00</th>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
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       "      <td>2018-01-19 00:00:00</td>\n",
       "      <td>2018-01-19</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
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       "      <td>2018-01-19</td>\n",
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       "      <td>2018-04-12 00:00:00</td>\n",
       "      <td>2018-04-12</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
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       "      <th rowspan=\"6\" valign=\"top\">2018-04-13 00:00:00</th>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>16789.9</td>\n",
       "      <td>2018-04-13 00:00:00</td>\n",
       "      <td>2018-04-13</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
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       "    <tr>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>6972.79</td>\n",
       "      <td>2018-04-13 00:00:00</td>\n",
       "      <td>2018-04-13</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>24753.9</td>\n",
       "      <td>2018-04-13 00:00:00</td>\n",
       "      <td>2018-04-13</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>19274.3</td>\n",
       "      <td>2018-04-13 00:00:00</td>\n",
       "      <td>2018-04-13</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>7143.09</td>\n",
       "      <td>2018-04-13 00:00:00</td>\n",
       "      <td>2018-04-13</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>14425.8</td>\n",
       "      <td>2018-04-13 00:00:00</td>\n",
       "      <td>2018-04-13</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-04-16 00:00:00</th>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>6011.11</td>\n",
       "      <td>2018-04-16 00:00:00</td>\n",
       "      <td>2018-04-16</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">2018-04-17 00:00:00</th>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>15587.8</td>\n",
       "      <td>2018-04-17 00:00:00</td>\n",
       "      <td>2018-04-17</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>20967.2</td>\n",
       "      <td>2018-04-17 00:00:00</td>\n",
       "      <td>2018-04-17</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>28099.7</td>\n",
       "      <td>2018-04-17 00:00:00</td>\n",
       "      <td>2018-04-17</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">2018-04-18 00:00:00</th>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>23742.1</td>\n",
       "      <td>2018-04-18 00:00:00</td>\n",
       "      <td>2018-04-18</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>11721.1</td>\n",
       "      <td>2018-04-18 00:00:00</td>\n",
       "      <td>2018-04-18</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>962.293</td>\n",
       "      <td>2018-04-18 00:00:00</td>\n",
       "      <td>2018-04-18</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">2018-04-20 00:00:00</th>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>12272.1</td>\n",
       "      <td>2018-04-20 00:00:00</td>\n",
       "      <td>2018-04-20</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>6792.48</td>\n",
       "      <td>2018-04-20 00:00:00</td>\n",
       "      <td>2018-04-20</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>18102.2</td>\n",
       "      <td>2018-04-20 00:00:00</td>\n",
       "      <td>2018-04-20</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>15006.8</td>\n",
       "      <td>2018-04-20 00:00:00</td>\n",
       "      <td>2018-04-20</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">2018-04-23 00:00:00</th>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>2535.04</td>\n",
       "      <td>2018-04-23 00:00:00</td>\n",
       "      <td>2018-04-23</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>5620.43</td>\n",
       "      <td>2018-04-23 00:00:00</td>\n",
       "      <td>2018-04-23</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-04-24 00:00:00</th>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>2535.04</td>\n",
       "      <td>2018-04-24 00:00:00</td>\n",
       "      <td>2018-04-24</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-04-25 00:00:00</th>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>32587.5</td>\n",
       "      <td>2018-04-25 00:00:00</td>\n",
       "      <td>2018-04-25</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"6\" valign=\"top\">2018-04-26 00:00:00</th>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>41883.8</td>\n",
       "      <td>2018-04-26 00:00:00</td>\n",
       "      <td>2018-04-26</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>34310.6</td>\n",
       "      <td>2018-04-26 00:00:00</td>\n",
       "      <td>2018-04-26</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>29742.6</td>\n",
       "      <td>2018-04-26 00:00:00</td>\n",
       "      <td>2018-04-26</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>18002.1</td>\n",
       "      <td>2018-04-26 00:00:00</td>\n",
       "      <td>2018-04-26</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>12923.2</td>\n",
       "      <td>2018-04-26 00:00:00</td>\n",
       "      <td>2018-04-26</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>531.54</td>\n",
       "      <td>2018-04-26 00:00:00</td>\n",
       "      <td>2018-04-26</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">2018-04-27 00:00:00</th>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>12191.9</td>\n",
       "      <td>2018-04-27 00:00:00</td>\n",
       "      <td>2018-04-27</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>50058.1</td>\n",
       "      <td>2018-04-27 00:00:00</td>\n",
       "      <td>2018-04-27</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>134 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                       cash             datetime       date  \\\n",
       "datetime            account_cookie                                            \n",
       "2018-01-02 00:00:00 JCSC_EXAMPLE     194080  2018-01-02 00:00:00 2018-01-02   \n",
       "                    JCSC_EXAMPLE     173263  2018-01-02 00:00:00 2018-01-02   \n",
       "                    JCSC_EXAMPLE     157386  2018-01-02 00:00:00 2018-01-02   \n",
       "                    JCSC_EXAMPLE     148660  2018-01-02 00:00:00 2018-01-02   \n",
       "                    JCSC_EXAMPLE     133243  2018-01-02 00:00:00 2018-01-02   \n",
       "                    JCSC_EXAMPLE     126652  2018-01-02 00:00:00 2018-01-02   \n",
       "                    JCSC_EXAMPLE     114761  2018-01-02 00:00:00 2018-01-02   \n",
       "2018-01-03 00:00:00 JCSC_EXAMPLE     105224  2018-01-03 00:00:00 2018-01-03   \n",
       "                    JCSC_EXAMPLE     101227  2018-01-03 00:00:00 2018-01-03   \n",
       "                    JCSC_EXAMPLE    92682.5  2018-01-03 00:00:00 2018-01-03   \n",
       "                    JCSC_EXAMPLE      62590  2018-01-03 00:00:00 2018-01-03   \n",
       "                    JCSC_EXAMPLE    46782.3  2018-01-03 00:00:00 2018-01-03   \n",
       "                    JCSC_EXAMPLE      35112  2018-01-03 00:00:00 2018-01-03   \n",
       "                    JCSC_EXAMPLE    20085.7  2018-01-03 00:00:00 2018-01-03   \n",
       "                    JCSC_EXAMPLE    2124.32  2018-01-03 00:00:00 2018-01-03   \n",
       "2018-01-09 00:00:00 JCSC_EXAMPLE    17060.4  2018-01-09 00:00:00 2018-01-09   \n",
       "2018-01-10 00:00:00 JCSC_EXAMPLE    3236.27  2018-01-10 00:00:00 2018-01-10   \n",
       "2018-01-12 00:00:00 JCSC_EXAMPLE      23111  2018-01-12 00:00:00 2018-01-12   \n",
       "                    JCSC_EXAMPLE    7233.25  2018-01-12 00:00:00 2018-01-12   \n",
       "2018-01-15 00:00:00 JCSC_EXAMPLE    21748.6  2018-01-15 00:00:00 2018-01-15   \n",
       "                    JCSC_EXAMPLE      35152  2018-01-15 00:00:00 2018-01-15   \n",
       "                    JCSC_EXAMPLE    43246.2  2018-01-15 00:00:00 2018-01-15   \n",
       "                    JCSC_EXAMPLE    53874.7  2018-01-15 00:00:00 2018-01-15   \n",
       "2018-01-16 00:00:00 JCSC_EXAMPLE    15207.2  2018-01-16 00:00:00 2018-01-16   \n",
       "                    JCSC_EXAMPLE    29852.8  2018-01-16 00:00:00 2018-01-16   \n",
       "                    JCSC_EXAMPLE    44147.7  2018-01-16 00:00:00 2018-01-16   \n",
       "                    JCSC_EXAMPLE    60686.6  2018-01-16 00:00:00 2018-01-16   \n",
       "2018-01-17 00:00:00 JCSC_EXAMPLE    51109.9  2018-01-17 00:00:00 2018-01-17   \n",
       "2018-01-19 00:00:00 JCSC_EXAMPLE    88034.4  2018-01-19 00:00:00 2018-01-19   \n",
       "                    JCSC_EXAMPLE    77686.3  2018-01-19 00:00:00 2018-01-19   \n",
       "...                                     ...                  ...        ...   \n",
       "2018-04-12 00:00:00 JCSC_EXAMPLE    421.348  2018-04-12 00:00:00 2018-04-12   \n",
       "2018-04-13 00:00:00 JCSC_EXAMPLE    16789.9  2018-04-13 00:00:00 2018-04-13   \n",
       "                    JCSC_EXAMPLE    6972.79  2018-04-13 00:00:00 2018-04-13   \n",
       "                    JCSC_EXAMPLE    24753.9  2018-04-13 00:00:00 2018-04-13   \n",
       "                    JCSC_EXAMPLE    19274.3  2018-04-13 00:00:00 2018-04-13   \n",
       "                    JCSC_EXAMPLE    7143.09  2018-04-13 00:00:00 2018-04-13   \n",
       "                    JCSC_EXAMPLE    14425.8  2018-04-13 00:00:00 2018-04-13   \n",
       "2018-04-16 00:00:00 JCSC_EXAMPLE    6011.11  2018-04-16 00:00:00 2018-04-16   \n",
       "2018-04-17 00:00:00 JCSC_EXAMPLE    15587.8  2018-04-17 00:00:00 2018-04-17   \n",
       "                    JCSC_EXAMPLE    20967.2  2018-04-17 00:00:00 2018-04-17   \n",
       "                    JCSC_EXAMPLE    28099.7  2018-04-17 00:00:00 2018-04-17   \n",
       "2018-04-18 00:00:00 JCSC_EXAMPLE    23742.1  2018-04-18 00:00:00 2018-04-18   \n",
       "                    JCSC_EXAMPLE    11721.1  2018-04-18 00:00:00 2018-04-18   \n",
       "                    JCSC_EXAMPLE    962.293  2018-04-18 00:00:00 2018-04-18   \n",
       "2018-04-20 00:00:00 JCSC_EXAMPLE    12272.1  2018-04-20 00:00:00 2018-04-20   \n",
       "                    JCSC_EXAMPLE    6792.48  2018-04-20 00:00:00 2018-04-20   \n",
       "                    JCSC_EXAMPLE    18102.2  2018-04-20 00:00:00 2018-04-20   \n",
       "                    JCSC_EXAMPLE    15006.8  2018-04-20 00:00:00 2018-04-20   \n",
       "2018-04-23 00:00:00 JCSC_EXAMPLE    2535.04  2018-04-23 00:00:00 2018-04-23   \n",
       "                    JCSC_EXAMPLE    5620.43  2018-04-23 00:00:00 2018-04-23   \n",
       "2018-04-24 00:00:00 JCSC_EXAMPLE    2535.04  2018-04-24 00:00:00 2018-04-24   \n",
       "2018-04-25 00:00:00 JCSC_EXAMPLE    32587.5  2018-04-25 00:00:00 2018-04-25   \n",
       "2018-04-26 00:00:00 JCSC_EXAMPLE    41883.8  2018-04-26 00:00:00 2018-04-26   \n",
       "                    JCSC_EXAMPLE    34310.6  2018-04-26 00:00:00 2018-04-26   \n",
       "                    JCSC_EXAMPLE    29742.6  2018-04-26 00:00:00 2018-04-26   \n",
       "                    JCSC_EXAMPLE    18002.1  2018-04-26 00:00:00 2018-04-26   \n",
       "                    JCSC_EXAMPLE    12923.2  2018-04-26 00:00:00 2018-04-26   \n",
       "                    JCSC_EXAMPLE     531.54  2018-04-26 00:00:00 2018-04-26   \n",
       "2018-04-27 00:00:00 JCSC_EXAMPLE    12191.9  2018-04-27 00:00:00 2018-04-27   \n",
       "                    JCSC_EXAMPLE    50058.1  2018-04-27 00:00:00 2018-04-27   \n",
       "\n",
       "                                   account_cookie  \n",
       "datetime            account_cookie                 \n",
       "2018-01-02 00:00:00 JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "                    JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "                    JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "                    JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "                    JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "                    JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "                    JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "2018-01-03 00:00:00 JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "                    JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "                    JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "                    JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "                    JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "                    JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "                    JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "                    JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "2018-01-09 00:00:00 JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "2018-01-10 00:00:00 JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "2018-01-12 00:00:00 JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "                    JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "2018-01-15 00:00:00 JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "                    JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "                    JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "                    JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "2018-01-16 00:00:00 JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "                    JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "                    JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "                    JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "2018-01-17 00:00:00 JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "2018-01-19 00:00:00 JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "                    JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "...                                           ...  \n",
       "2018-04-12 00:00:00 JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "2018-04-13 00:00:00 JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "                    JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "                    JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "                    JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "                    JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "                    JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "2018-04-16 00:00:00 JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "2018-04-17 00:00:00 JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "                    JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "                    JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "2018-04-18 00:00:00 JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "                    JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "                    JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "2018-04-20 00:00:00 JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "                    JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "                    JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "                    JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "2018-04-23 00:00:00 JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "                    JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "2018-04-24 00:00:00 JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "2018-04-25 00:00:00 JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "2018-04-26 00:00:00 JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "                    JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "                    JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "                    JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "                    JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "                    JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "2018-04-27 00:00:00 JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "                    JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "\n",
       "[134 rows x 4 columns]"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Risk.account.cash_table"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "date        account_cookie\n",
       "2018-01-02  JCSC_EXAMPLE       85090.000000\n",
       "2018-01-03  JCSC_EXAMPLE      199920.000000\n",
       "2018-01-09  JCSC_EXAMPLE      181770.000000\n",
       "2018-01-10  JCSC_EXAMPLE      195190.000000\n",
       "2018-01-12  JCSC_EXAMPLE      192210.000000\n",
       "2018-01-15  JCSC_EXAMPLE      140640.000000\n",
       "2018-01-16  JCSC_EXAMPLE      134750.000000\n",
       "2018-01-17  JCSC_EXAMPLE      139840.000000\n",
       "2018-01-19  JCSC_EXAMPLE      137370.000000\n",
       "2018-01-22  JCSC_EXAMPLE      193990.000000\n",
       "2018-01-23  JCSC_EXAMPLE      180630.000000\n",
       "2018-01-24  JCSC_EXAMPLE      200790.000000\n",
       "2018-01-25  JCSC_EXAMPLE      203080.000000\n",
       "2018-01-29  JCSC_EXAMPLE      197540.000000\n",
       "2018-01-31  JCSC_EXAMPLE      156950.000000\n",
       "2018-02-01  JCSC_EXAMPLE       86030.000000\n",
       "2018-02-02  JCSC_EXAMPLE      161320.000000\n",
       "2018-02-06  JCSC_EXAMPLE      115810.000000\n",
       "2018-02-07  JCSC_EXAMPLE      141093.410774\n",
       "2018-02-08  JCSC_EXAMPLE      168030.978742\n",
       "2018-02-12  JCSC_EXAMPLE      190451.008401\n",
       "2018-02-22  JCSC_EXAMPLE      208569.911021\n",
       "2018-03-02  JCSC_EXAMPLE      154247.034105\n",
       "2018-03-07  JCSC_EXAMPLE      132857.034105\n",
       "2018-03-09  JCSC_EXAMPLE      170975.106275\n",
       "2018-03-12  JCSC_EXAMPLE      197694.869004\n",
       "2018-03-14  JCSC_EXAMPLE      132957.923873\n",
       "2018-03-16  JCSC_EXAMPLE       59280.000000\n",
       "2018-03-19  JCSC_EXAMPLE       70200.000000\n",
       "2018-03-20  JCSC_EXAMPLE       66798.330047\n",
       "2018-03-21  JCSC_EXAMPLE       91246.157620\n",
       "2018-03-22  JCSC_EXAMPLE      130987.379610\n",
       "2018-03-23  JCSC_EXAMPLE       61718.289314\n",
       "2018-03-26  JCSC_EXAMPLE      185195.338417\n",
       "2018-03-27  JCSC_EXAMPLE      198254.750918\n",
       "2018-04-04  JCSC_EXAMPLE      113569.600121\n",
       "2018-04-09  JCSC_EXAMPLE      195960.052687\n",
       "2018-04-10  JCSC_EXAMPLE       94314.194214\n",
       "2018-04-11  JCSC_EXAMPLE      183575.709557\n",
       "2018-04-12  JCSC_EXAMPLE      189996.021844\n",
       "2018-04-13  JCSC_EXAMPLE      177460.000000\n",
       "2018-04-16  JCSC_EXAMPLE      189340.000000\n",
       "2018-04-17  JCSC_EXAMPLE      164860.000000\n",
       "2018-04-18  JCSC_EXAMPLE      198380.000000\n",
       "2018-04-20  JCSC_EXAMPLE      181360.000000\n",
       "2018-04-23  JCSC_EXAMPLE      185250.000000\n",
       "2018-04-24  JCSC_EXAMPLE      193410.000000\n",
       "2018-04-25  JCSC_EXAMPLE      164030.000000\n",
       "2018-04-26  JCSC_EXAMPLE      192220.000000\n",
       "2018-04-27  JCSC_EXAMPLE      139970.000000\n",
       "dtype: float64"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Risk.market_value.sum(axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>datetime</th>\n",
       "      <th>code</th>\n",
       "      <th>price</th>\n",
       "      <th>amount</th>\n",
       "      <th>cash</th>\n",
       "      <th>order_id</th>\n",
       "      <th>realorder_id</th>\n",
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       "      <th>account_cookie</th>\n",
       "      <th>commission</th>\n",
       "      <th>tax</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2018-01-02 00:00:00</td>\n",
       "      <td>002195</td>\n",
       "      <td>5.91</td>\n",
       "      <td>1000</td>\n",
       "      <td>194079.6575</td>\n",
       "      <td>Order_AGZefuXd</td>\n",
       "      <td>Order_AGZefuXd</td>\n",
       "      <td>Trade_7RxnPTq1</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>1.4775</td>\n",
       "      <td>8.865</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2018-01-02 00:00:00</td>\n",
       "      <td>002456</td>\n",
       "      <td>20.78</td>\n",
       "      <td>1000</td>\n",
       "      <td>173263.2925</td>\n",
       "      <td>Order_qOuEB4fo</td>\n",
       "      <td>Order_qOuEB4fo</td>\n",
       "      <td>Trade_5IZEW2LB</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>5.1950</td>\n",
       "      <td>31.170</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2018-01-02 00:00:00</td>\n",
       "      <td>002544</td>\n",
       "      <td>15.85</td>\n",
       "      <td>1000</td>\n",
       "      <td>157385.5550</td>\n",
       "      <td>Order_ripYwt6L</td>\n",
       "      <td>Order_ripYwt6L</td>\n",
       "      <td>Trade_VzvpFjPM</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>3.9625</td>\n",
       "      <td>23.775</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2018-01-02 00:00:00</td>\n",
       "      <td>300290</td>\n",
       "      <td>8.71</td>\n",
       "      <td>1000</td>\n",
       "      <td>148660.3125</td>\n",
       "      <td>Order_ph50Tje9</td>\n",
       "      <td>Order_ph50Tje9</td>\n",
       "      <td>Trade_vWYaMmhq</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>2.1775</td>\n",
       "      <td>13.065</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2018-01-02 00:00:00</td>\n",
       "      <td>300367</td>\n",
       "      <td>15.39</td>\n",
       "      <td>1000</td>\n",
       "      <td>133243.3800</td>\n",
       "      <td>Order_YvlByWfD</td>\n",
       "      <td>Order_YvlByWfD</td>\n",
       "      <td>Trade_zWlyg0UM</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>3.8475</td>\n",
       "      <td>23.085</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2018-01-02 00:00:00</td>\n",
       "      <td>600105</td>\n",
       "      <td>6.58</td>\n",
       "      <td>1000</td>\n",
       "      <td>126651.8650</td>\n",
       "      <td>Order_8sBTIvLO</td>\n",
       "      <td>Order_8sBTIvLO</td>\n",
       "      <td>Trade_cay7rZ6J</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>1.6450</td>\n",
       "      <td>9.870</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2018-01-02 00:00:00</td>\n",
       "      <td>600797</td>\n",
       "      <td>11.87</td>\n",
       "      <td>1000</td>\n",
       "      <td>114761.0925</td>\n",
       "      <td>Order_whQIWHBi</td>\n",
       "      <td>Order_whQIWHBi</td>\n",
       "      <td>Trade_NtWVGFSo</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>2.9675</td>\n",
       "      <td>17.805</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2018-01-03 00:00:00</td>\n",
       "      <td>000070</td>\n",
       "      <td>9.52</td>\n",
       "      <td>1000</td>\n",
       "      <td>105224.4325</td>\n",
       "      <td>Order_wDPTJiRh</td>\n",
       "      <td>Order_wDPTJiRh</td>\n",
       "      <td>Trade_eufovKcX</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>2.3800</td>\n",
       "      <td>14.280</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2018-01-03 00:00:00</td>\n",
       "      <td>000100</td>\n",
       "      <td>3.99</td>\n",
       "      <td>1000</td>\n",
       "      <td>101227.4500</td>\n",
       "      <td>Order_f8yNTPHe</td>\n",
       "      <td>Order_f8yNTPHe</td>\n",
       "      <td>Trade_OUEDoFnu</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>0.9975</td>\n",
       "      <td>5.985</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2018-01-03 00:00:00</td>\n",
       "      <td>002065</td>\n",
       "      <td>8.53</td>\n",
       "      <td>1000</td>\n",
       "      <td>92682.5225</td>\n",
       "      <td>Order_x5k8PvbA</td>\n",
       "      <td>Order_x5k8PvbA</td>\n",
       "      <td>Trade_dBbge5v4</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>2.1325</td>\n",
       "      <td>12.795</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2018-01-03 00:00:00</td>\n",
       "      <td>002335</td>\n",
       "      <td>30.04</td>\n",
       "      <td>1000</td>\n",
       "      <td>62589.9525</td>\n",
       "      <td>Order_jKYkEcmX</td>\n",
       "      <td>Order_jKYkEcmX</td>\n",
       "      <td>Trade_L1dMti6K</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>7.5100</td>\n",
       "      <td>45.060</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2018-01-03 00:00:00</td>\n",
       "      <td>300036</td>\n",
       "      <td>15.78</td>\n",
       "      <td>1000</td>\n",
       "      <td>46782.3375</td>\n",
       "      <td>Order_iB3KzEPv</td>\n",
       "      <td>Order_iB3KzEPv</td>\n",
       "      <td>Trade_rXCb1PJu</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>3.9450</td>\n",
       "      <td>23.670</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>2018-01-03 00:00:00</td>\n",
       "      <td>600198</td>\n",
       "      <td>11.65</td>\n",
       "      <td>1000</td>\n",
       "      <td>35111.9500</td>\n",
       "      <td>Order_eFZH05bs</td>\n",
       "      <td>Order_eFZH05bs</td>\n",
       "      <td>Trade_nHqFwT30</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>2.9125</td>\n",
       "      <td>17.475</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>2018-01-03 00:00:00</td>\n",
       "      <td>600718</td>\n",
       "      <td>15.00</td>\n",
       "      <td>1000</td>\n",
       "      <td>20085.7000</td>\n",
       "      <td>Order_K3MjyXZo</td>\n",
       "      <td>Order_K3MjyXZo</td>\n",
       "      <td>Trade_zrGbK97E</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>3.7500</td>\n",
       "      <td>22.500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>2018-01-03 00:00:00</td>\n",
       "      <td>600804</td>\n",
       "      <td>17.93</td>\n",
       "      <td>1000</td>\n",
       "      <td>2124.3225</td>\n",
       "      <td>Order_EdD6u1Cb</td>\n",
       "      <td>Order_EdD6u1Cb</td>\n",
       "      <td>Trade_Bw0n39H5</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>4.4825</td>\n",
       "      <td>26.895</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>2018-01-09 00:00:00</td>\n",
       "      <td>300367</td>\n",
       "      <td>14.91</td>\n",
       "      <td>-1000</td>\n",
       "      <td>17060.4150</td>\n",
       "      <td>Order_KYdA3NQ9</td>\n",
       "      <td>Order_KYdA3NQ9</td>\n",
       "      <td>Trade_rf1oEbiF</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>-3.7275</td>\n",
       "      <td>-22.365</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>2018-01-10 00:00:00</td>\n",
       "      <td>300245</td>\n",
       "      <td>13.80</td>\n",
       "      <td>1000</td>\n",
       "      <td>3236.2650</td>\n",
       "      <td>Order_uCE5pWke</td>\n",
       "      <td>Order_uCE5pWke</td>\n",
       "      <td>Trade_ZGCEmfb8</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>3.4500</td>\n",
       "      <td>20.700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>2018-01-12 00:00:00</td>\n",
       "      <td>002456</td>\n",
       "      <td>19.84</td>\n",
       "      <td>-1000</td>\n",
       "      <td>23110.9850</td>\n",
       "      <td>Order_p5J1Paxo</td>\n",
       "      <td>Order_p5J1Paxo</td>\n",
       "      <td>Trade_1quYOxnZ</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>-4.9600</td>\n",
       "      <td>-29.760</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>2018-01-12 00:00:00</td>\n",
       "      <td>300052</td>\n",
       "      <td>15.85</td>\n",
       "      <td>1000</td>\n",
       "      <td>7233.2475</td>\n",
       "      <td>Order_GOfSMKya</td>\n",
       "      <td>Order_GOfSMKya</td>\n",
       "      <td>Trade_PIZ23WAV</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>3.9625</td>\n",
       "      <td>23.775</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>2018-01-15 00:00:00</td>\n",
       "      <td>300036</td>\n",
       "      <td>14.49</td>\n",
       "      <td>-1000</td>\n",
       "      <td>21748.6050</td>\n",
       "      <td>Order_kK1V8DEQ</td>\n",
       "      <td>Order_kK1V8DEQ</td>\n",
       "      <td>Trade_3Cq2vZib</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>-3.6225</td>\n",
       "      <td>-21.735</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>2018-01-15 00:00:00</td>\n",
       "      <td>300245</td>\n",
       "      <td>13.38</td>\n",
       "      <td>-1000</td>\n",
       "      <td>35152.0200</td>\n",
       "      <td>Order_qcGuE2ij</td>\n",
       "      <td>Order_qcGuE2ij</td>\n",
       "      <td>Trade_ubTdkr14</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>-3.3450</td>\n",
       "      <td>-20.070</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>2018-01-15 00:00:00</td>\n",
       "      <td>300290</td>\n",
       "      <td>8.08</td>\n",
       "      <td>-1000</td>\n",
       "      <td>43246.1600</td>\n",
       "      <td>Order_XAcLutCp</td>\n",
       "      <td>Order_XAcLutCp</td>\n",
       "      <td>Trade_OjA3lpNn</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>-2.0200</td>\n",
       "      <td>-12.120</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>2018-01-15 00:00:00</td>\n",
       "      <td>600198</td>\n",
       "      <td>10.61</td>\n",
       "      <td>-1000</td>\n",
       "      <td>53874.7275</td>\n",
       "      <td>Order_VXd1B3KE</td>\n",
       "      <td>Order_VXd1B3KE</td>\n",
       "      <td>Trade_KqQpcCGy</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>-2.6525</td>\n",
       "      <td>-15.915</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>2018-01-16 00:00:00</td>\n",
       "      <td>000063</td>\n",
       "      <td>38.60</td>\n",
       "      <td>1000</td>\n",
       "      <td>15207.1775</td>\n",
       "      <td>Order_xfhHbnI0</td>\n",
       "      <td>Order_xfhHbnI0</td>\n",
       "      <td>Trade_2ctPwXGN</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>9.6500</td>\n",
       "      <td>57.900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>2018-01-16 00:00:00</td>\n",
       "      <td>002544</td>\n",
       "      <td>14.62</td>\n",
       "      <td>-1000</td>\n",
       "      <td>29852.7625</td>\n",
       "      <td>Order_ydeshXSg</td>\n",
       "      <td>Order_ydeshXSg</td>\n",
       "      <td>Trade_JgWf6d1e</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>-3.6550</td>\n",
       "      <td>-21.930</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>2018-01-16 00:00:00</td>\n",
       "      <td>600718</td>\n",
       "      <td>14.27</td>\n",
       "      <td>-1000</td>\n",
       "      <td>44147.7350</td>\n",
       "      <td>Order_tWCmXwzc</td>\n",
       "      <td>Order_tWCmXwzc</td>\n",
       "      <td>Trade_0jDlCpSA</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>-3.5675</td>\n",
       "      <td>-21.405</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>2018-01-16 00:00:00</td>\n",
       "      <td>600804</td>\n",
       "      <td>16.51</td>\n",
       "      <td>-1000</td>\n",
       "      <td>60686.6275</td>\n",
       "      <td>Order_tZncUvNb</td>\n",
       "      <td>Order_tZncUvNb</td>\n",
       "      <td>Trade_ChUqo3HI</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>-4.1275</td>\n",
       "      <td>-24.765</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>2018-01-17 00:00:00</td>\n",
       "      <td>300297</td>\n",
       "      <td>9.56</td>\n",
       "      <td>1000</td>\n",
       "      <td>51109.8975</td>\n",
       "      <td>Order_X3FLjoUW</td>\n",
       "      <td>Order_X3FLjoUW</td>\n",
       "      <td>Trade_qtGE2dYw</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>2.3900</td>\n",
       "      <td>14.340</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>2018-01-19 00:00:00</td>\n",
       "      <td>000063</td>\n",
       "      <td>36.86</td>\n",
       "      <td>-1000</td>\n",
       "      <td>88034.4025</td>\n",
       "      <td>Order_gwUSRf3G</td>\n",
       "      <td>Order_gwUSRf3G</td>\n",
       "      <td>Trade_jTevtxld</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>-9.2150</td>\n",
       "      <td>-55.290</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>2018-01-19 00:00:00</td>\n",
       "      <td>002279</td>\n",
       "      <td>10.33</td>\n",
       "      <td>1000</td>\n",
       "      <td>77686.3250</td>\n",
       "      <td>Order_nuivkPTW</td>\n",
       "      <td>Order_nuivkPTW</td>\n",
       "      <td>Trade_PKRkTfIc</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>2.5825</td>\n",
       "      <td>15.495</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>104</th>\n",
       "      <td>2018-04-12 00:00:00</td>\n",
       "      <td>600198</td>\n",
       "      <td>8.32</td>\n",
       "      <td>1000</td>\n",
       "      <td>421.3475</td>\n",
       "      <td>Order_pjNsHFm5</td>\n",
       "      <td>Order_pjNsHFm5</td>\n",
       "      <td>Trade_KdhnNHOe</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>2.0800</td>\n",
       "      <td>12.480</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>105</th>\n",
       "      <td>2018-04-13 00:00:00</td>\n",
       "      <td>300085</td>\n",
       "      <td>16.34</td>\n",
       "      <td>-1000</td>\n",
       "      <td>16789.9425</td>\n",
       "      <td>Order_g3w6Eir7</td>\n",
       "      <td>Order_g3w6Eir7</td>\n",
       "      <td>Trade_j2tT6B3x</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>-4.0850</td>\n",
       "      <td>-24.510</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>106</th>\n",
       "      <td>2018-04-13 00:00:00</td>\n",
       "      <td>300287</td>\n",
       "      <td>9.80</td>\n",
       "      <td>1000</td>\n",
       "      <td>6972.7925</td>\n",
       "      <td>Order_vi4usBEU</td>\n",
       "      <td>Order_vi4usBEU</td>\n",
       "      <td>Trade_8NPLyuqB</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>2.4500</td>\n",
       "      <td>14.700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>107</th>\n",
       "      <td>2018-04-13 00:00:00</td>\n",
       "      <td>300383</td>\n",
       "      <td>17.75</td>\n",
       "      <td>-1000</td>\n",
       "      <td>24753.8550</td>\n",
       "      <td>Order_avKOAeWI</td>\n",
       "      <td>Order_avKOAeWI</td>\n",
       "      <td>Trade_UvTz98l6</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>-4.4375</td>\n",
       "      <td>-26.625</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>108</th>\n",
       "      <td>2018-04-13 00:00:00</td>\n",
       "      <td>600589</td>\n",
       "      <td>5.47</td>\n",
       "      <td>1000</td>\n",
       "      <td>19274.2825</td>\n",
       "      <td>Order_kLGItRjr</td>\n",
       "      <td>Order_kLGItRjr</td>\n",
       "      <td>Trade_XwPiIrMC</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>1.3675</td>\n",
       "      <td>8.205</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>109</th>\n",
       "      <td>2018-04-13 00:00:00</td>\n",
       "      <td>600590</td>\n",
       "      <td>12.11</td>\n",
       "      <td>1000</td>\n",
       "      <td>7143.0900</td>\n",
       "      <td>Order_E2Vx6M3o</td>\n",
       "      <td>Order_E2Vx6M3o</td>\n",
       "      <td>Trade_IuTMkVep</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>3.0275</td>\n",
       "      <td>18.165</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110</th>\n",
       "      <td>2018-04-13 00:00:00</td>\n",
       "      <td>601928</td>\n",
       "      <td>7.27</td>\n",
       "      <td>-1000</td>\n",
       "      <td>14425.8125</td>\n",
       "      <td>Order_XLp31JS6</td>\n",
       "      <td>Order_XLp31JS6</td>\n",
       "      <td>Trade_R87jVyex</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>-1.8175</td>\n",
       "      <td>-10.905</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>111</th>\n",
       "      <td>2018-04-16 00:00:00</td>\n",
       "      <td>002065</td>\n",
       "      <td>8.40</td>\n",
       "      <td>1000</td>\n",
       "      <td>6011.1125</td>\n",
       "      <td>Order_ubHjJ3Tr</td>\n",
       "      <td>Order_ubHjJ3Tr</td>\n",
       "      <td>Trade_jTY5sS7D</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>2.1000</td>\n",
       "      <td>12.600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>112</th>\n",
       "      <td>2018-04-17 00:00:00</td>\n",
       "      <td>300287</td>\n",
       "      <td>9.56</td>\n",
       "      <td>-1000</td>\n",
       "      <td>15587.8425</td>\n",
       "      <td>Order_myObDLoh</td>\n",
       "      <td>Order_myObDLoh</td>\n",
       "      <td>Trade_ds7iXu4V</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>-2.3900</td>\n",
       "      <td>-14.340</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113</th>\n",
       "      <td>2018-04-17 00:00:00</td>\n",
       "      <td>600589</td>\n",
       "      <td>5.37</td>\n",
       "      <td>-1000</td>\n",
       "      <td>20967.2400</td>\n",
       "      <td>Order_fzOQt846</td>\n",
       "      <td>Order_fzOQt846</td>\n",
       "      <td>Trade_DQlIEonw</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>-1.3425</td>\n",
       "      <td>-8.055</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>114</th>\n",
       "      <td>2018-04-17 00:00:00</td>\n",
       "      <td>600770</td>\n",
       "      <td>7.12</td>\n",
       "      <td>-1000</td>\n",
       "      <td>28099.7000</td>\n",
       "      <td>Order_Ae5XduIP</td>\n",
       "      <td>Order_Ae5XduIP</td>\n",
       "      <td>Trade_amJjUL0o</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>-1.7800</td>\n",
       "      <td>-10.680</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>115</th>\n",
       "      <td>2018-04-18 00:00:00</td>\n",
       "      <td>002463</td>\n",
       "      <td>4.35</td>\n",
       "      <td>1000</td>\n",
       "      <td>23742.0875</td>\n",
       "      <td>Order_X7xe5kOH</td>\n",
       "      <td>Order_X7xe5kOH</td>\n",
       "      <td>Trade_TVimMICX</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>1.0875</td>\n",
       "      <td>6.525</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>116</th>\n",
       "      <td>2018-04-18 00:00:00</td>\n",
       "      <td>300051</td>\n",
       "      <td>12.00</td>\n",
       "      <td>1000</td>\n",
       "      <td>11721.0875</td>\n",
       "      <td>Order_pcYyubnM</td>\n",
       "      <td>Order_pcYyubnM</td>\n",
       "      <td>Trade_R1KrCWaw</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>3.0000</td>\n",
       "      <td>18.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>117</th>\n",
       "      <td>2018-04-18 00:00:00</td>\n",
       "      <td>600100</td>\n",
       "      <td>10.74</td>\n",
       "      <td>1000</td>\n",
       "      <td>962.2925</td>\n",
       "      <td>Order_fR1zVgNU</td>\n",
       "      <td>Order_fR1zVgNU</td>\n",
       "      <td>Trade_cj2bPWtZ</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>2.6850</td>\n",
       "      <td>16.110</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>118</th>\n",
       "      <td>2018-04-20 00:00:00</td>\n",
       "      <td>300051</td>\n",
       "      <td>11.29</td>\n",
       "      <td>-1000</td>\n",
       "      <td>12272.0500</td>\n",
       "      <td>Order_7g6uwcl4</td>\n",
       "      <td>Order_7g6uwcl4</td>\n",
       "      <td>Trade_OaPhtvDf</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>-2.8225</td>\n",
       "      <td>-16.935</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>119</th>\n",
       "      <td>2018-04-20 00:00:00</td>\n",
       "      <td>600589</td>\n",
       "      <td>5.47</td>\n",
       "      <td>1000</td>\n",
       "      <td>6792.4775</td>\n",
       "      <td>Order_p5UcQmBw</td>\n",
       "      <td>Order_p5UcQmBw</td>\n",
       "      <td>Trade_6fkmJV4P</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>1.3675</td>\n",
       "      <td>8.205</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>120</th>\n",
       "      <td>2018-04-20 00:00:00</td>\n",
       "      <td>600590</td>\n",
       "      <td>11.29</td>\n",
       "      <td>-1000</td>\n",
       "      <td>18102.2350</td>\n",
       "      <td>Order_img5TnKy</td>\n",
       "      <td>Order_img5TnKy</td>\n",
       "      <td>Trade_fjUkgyIM</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>-2.8225</td>\n",
       "      <td>-16.935</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>121</th>\n",
       "      <td>2018-04-20 00:00:00</td>\n",
       "      <td>600601</td>\n",
       "      <td>3.09</td>\n",
       "      <td>1000</td>\n",
       "      <td>15006.8275</td>\n",
       "      <td>Order_dI9SJy3q</td>\n",
       "      <td>Order_dI9SJy3q</td>\n",
       "      <td>Trade_S7k6KvgN</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>0.7725</td>\n",
       "      <td>4.635</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>122</th>\n",
       "      <td>2018-04-23 00:00:00</td>\n",
       "      <td>300366</td>\n",
       "      <td>12.45</td>\n",
       "      <td>1000</td>\n",
       "      <td>2535.0400</td>\n",
       "      <td>Order_k2rIMafR</td>\n",
       "      <td>Order_k2rIMafR</td>\n",
       "      <td>Trade_NVH6ZrhU</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>3.1125</td>\n",
       "      <td>18.675</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>123</th>\n",
       "      <td>2018-04-23 00:00:00</td>\n",
       "      <td>600601</td>\n",
       "      <td>3.08</td>\n",
       "      <td>-1000</td>\n",
       "      <td>5620.4300</td>\n",
       "      <td>Order_dtTBM43Y</td>\n",
       "      <td>Order_dtTBM43Y</td>\n",
       "      <td>Trade_VchbZSEH</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>-0.7700</td>\n",
       "      <td>-4.620</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>124</th>\n",
       "      <td>2018-04-24 00:00:00</td>\n",
       "      <td>600601</td>\n",
       "      <td>3.08</td>\n",
       "      <td>1000</td>\n",
       "      <td>2535.0400</td>\n",
       "      <td>Order_xrFNEVC4</td>\n",
       "      <td>Order_xrFNEVC4</td>\n",
       "      <td>Trade_BlUXpNAc</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>0.7700</td>\n",
       "      <td>4.620</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>125</th>\n",
       "      <td>2018-04-25 00:00:00</td>\n",
       "      <td>600845</td>\n",
       "      <td>30.00</td>\n",
       "      <td>-1000</td>\n",
       "      <td>32587.5400</td>\n",
       "      <td>Order_qm1vYekP</td>\n",
       "      <td>Order_qm1vYekP</td>\n",
       "      <td>Trade_Z8PMI0wO</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>-7.5000</td>\n",
       "      <td>-45.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>126</th>\n",
       "      <td>2018-04-26 00:00:00</td>\n",
       "      <td>000066</td>\n",
       "      <td>9.28</td>\n",
       "      <td>-1000</td>\n",
       "      <td>41883.7800</td>\n",
       "      <td>Order_Q5H2Fkrm</td>\n",
       "      <td>Order_Q5H2Fkrm</td>\n",
       "      <td>Trade_5kSnPrJ0</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>-2.3200</td>\n",
       "      <td>-13.920</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>127</th>\n",
       "      <td>2018-04-26 00:00:00</td>\n",
       "      <td>000611</td>\n",
       "      <td>7.56</td>\n",
       "      <td>1000</td>\n",
       "      <td>34310.5500</td>\n",
       "      <td>Order_5vLmotrf</td>\n",
       "      <td>Order_5vLmotrf</td>\n",
       "      <td>Trade_9aXfk1ur</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>1.8900</td>\n",
       "      <td>11.340</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>128</th>\n",
       "      <td>2018-04-26 00:00:00</td>\n",
       "      <td>000836</td>\n",
       "      <td>4.56</td>\n",
       "      <td>1000</td>\n",
       "      <td>29742.5700</td>\n",
       "      <td>Order_8c0vIeK3</td>\n",
       "      <td>Order_8c0vIeK3</td>\n",
       "      <td>Trade_aez4PKrt</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>1.1400</td>\n",
       "      <td>6.840</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>129</th>\n",
       "      <td>2018-04-26 00:00:00</td>\n",
       "      <td>002063</td>\n",
       "      <td>11.72</td>\n",
       "      <td>1000</td>\n",
       "      <td>18002.0600</td>\n",
       "      <td>Order_v26iRnZQ</td>\n",
       "      <td>Order_v26iRnZQ</td>\n",
       "      <td>Trade_CtKujRbr</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>2.9300</td>\n",
       "      <td>17.580</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>130</th>\n",
       "      <td>2018-04-26 00:00:00</td>\n",
       "      <td>300025</td>\n",
       "      <td>5.07</td>\n",
       "      <td>1000</td>\n",
       "      <td>12923.1875</td>\n",
       "      <td>Order_U1mKR6OG</td>\n",
       "      <td>Order_U1mKR6OG</td>\n",
       "      <td>Trade_18JMpRnG</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>1.2675</td>\n",
       "      <td>7.605</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>131</th>\n",
       "      <td>2018-04-26 00:00:00</td>\n",
       "      <td>300235</td>\n",
       "      <td>12.37</td>\n",
       "      <td>1000</td>\n",
       "      <td>531.5400</td>\n",
       "      <td>Order_8HUWfJx1</td>\n",
       "      <td>Order_8HUWfJx1</td>\n",
       "      <td>Trade_WPNlvA1E</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>3.0925</td>\n",
       "      <td>18.555</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>132</th>\n",
       "      <td>2018-04-27 00:00:00</td>\n",
       "      <td>002063</td>\n",
       "      <td>11.64</td>\n",
       "      <td>-1000</td>\n",
       "      <td>12191.9100</td>\n",
       "      <td>Order_BtPZvUWw</td>\n",
       "      <td>Order_BtPZvUWw</td>\n",
       "      <td>Trade_ICkVoQOZ</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>-2.9100</td>\n",
       "      <td>-17.460</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>133</th>\n",
       "      <td>2018-04-27 00:00:00</td>\n",
       "      <td>601360</td>\n",
       "      <td>37.80</td>\n",
       "      <td>-1000</td>\n",
       "      <td>50058.0600</td>\n",
       "      <td>Order_lyDrw7iT</td>\n",
       "      <td>Order_lyDrw7iT</td>\n",
       "      <td>Trade_3aozRWnk</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "      <td>-9.4500</td>\n",
       "      <td>-56.700</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>134 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                datetime    code  price  amount         cash        order_id  \\\n",
       "0    2018-01-02 00:00:00  002195   5.91    1000  194079.6575  Order_AGZefuXd   \n",
       "1    2018-01-02 00:00:00  002456  20.78    1000  173263.2925  Order_qOuEB4fo   \n",
       "2    2018-01-02 00:00:00  002544  15.85    1000  157385.5550  Order_ripYwt6L   \n",
       "3    2018-01-02 00:00:00  300290   8.71    1000  148660.3125  Order_ph50Tje9   \n",
       "4    2018-01-02 00:00:00  300367  15.39    1000  133243.3800  Order_YvlByWfD   \n",
       "5    2018-01-02 00:00:00  600105   6.58    1000  126651.8650  Order_8sBTIvLO   \n",
       "6    2018-01-02 00:00:00  600797  11.87    1000  114761.0925  Order_whQIWHBi   \n",
       "7    2018-01-03 00:00:00  000070   9.52    1000  105224.4325  Order_wDPTJiRh   \n",
       "8    2018-01-03 00:00:00  000100   3.99    1000  101227.4500  Order_f8yNTPHe   \n",
       "9    2018-01-03 00:00:00  002065   8.53    1000   92682.5225  Order_x5k8PvbA   \n",
       "10   2018-01-03 00:00:00  002335  30.04    1000   62589.9525  Order_jKYkEcmX   \n",
       "11   2018-01-03 00:00:00  300036  15.78    1000   46782.3375  Order_iB3KzEPv   \n",
       "12   2018-01-03 00:00:00  600198  11.65    1000   35111.9500  Order_eFZH05bs   \n",
       "13   2018-01-03 00:00:00  600718  15.00    1000   20085.7000  Order_K3MjyXZo   \n",
       "14   2018-01-03 00:00:00  600804  17.93    1000    2124.3225  Order_EdD6u1Cb   \n",
       "15   2018-01-09 00:00:00  300367  14.91   -1000   17060.4150  Order_KYdA3NQ9   \n",
       "16   2018-01-10 00:00:00  300245  13.80    1000    3236.2650  Order_uCE5pWke   \n",
       "17   2018-01-12 00:00:00  002456  19.84   -1000   23110.9850  Order_p5J1Paxo   \n",
       "18   2018-01-12 00:00:00  300052  15.85    1000    7233.2475  Order_GOfSMKya   \n",
       "19   2018-01-15 00:00:00  300036  14.49   -1000   21748.6050  Order_kK1V8DEQ   \n",
       "20   2018-01-15 00:00:00  300245  13.38   -1000   35152.0200  Order_qcGuE2ij   \n",
       "21   2018-01-15 00:00:00  300290   8.08   -1000   43246.1600  Order_XAcLutCp   \n",
       "22   2018-01-15 00:00:00  600198  10.61   -1000   53874.7275  Order_VXd1B3KE   \n",
       "23   2018-01-16 00:00:00  000063  38.60    1000   15207.1775  Order_xfhHbnI0   \n",
       "24   2018-01-16 00:00:00  002544  14.62   -1000   29852.7625  Order_ydeshXSg   \n",
       "25   2018-01-16 00:00:00  600718  14.27   -1000   44147.7350  Order_tWCmXwzc   \n",
       "26   2018-01-16 00:00:00  600804  16.51   -1000   60686.6275  Order_tZncUvNb   \n",
       "27   2018-01-17 00:00:00  300297   9.56    1000   51109.8975  Order_X3FLjoUW   \n",
       "28   2018-01-19 00:00:00  000063  36.86   -1000   88034.4025  Order_gwUSRf3G   \n",
       "29   2018-01-19 00:00:00  002279  10.33    1000   77686.3250  Order_nuivkPTW   \n",
       "..                   ...     ...    ...     ...          ...             ...   \n",
       "104  2018-04-12 00:00:00  600198   8.32    1000     421.3475  Order_pjNsHFm5   \n",
       "105  2018-04-13 00:00:00  300085  16.34   -1000   16789.9425  Order_g3w6Eir7   \n",
       "106  2018-04-13 00:00:00  300287   9.80    1000    6972.7925  Order_vi4usBEU   \n",
       "107  2018-04-13 00:00:00  300383  17.75   -1000   24753.8550  Order_avKOAeWI   \n",
       "108  2018-04-13 00:00:00  600589   5.47    1000   19274.2825  Order_kLGItRjr   \n",
       "109  2018-04-13 00:00:00  600590  12.11    1000    7143.0900  Order_E2Vx6M3o   \n",
       "110  2018-04-13 00:00:00  601928   7.27   -1000   14425.8125  Order_XLp31JS6   \n",
       "111  2018-04-16 00:00:00  002065   8.40    1000    6011.1125  Order_ubHjJ3Tr   \n",
       "112  2018-04-17 00:00:00  300287   9.56   -1000   15587.8425  Order_myObDLoh   \n",
       "113  2018-04-17 00:00:00  600589   5.37   -1000   20967.2400  Order_fzOQt846   \n",
       "114  2018-04-17 00:00:00  600770   7.12   -1000   28099.7000  Order_Ae5XduIP   \n",
       "115  2018-04-18 00:00:00  002463   4.35    1000   23742.0875  Order_X7xe5kOH   \n",
       "116  2018-04-18 00:00:00  300051  12.00    1000   11721.0875  Order_pcYyubnM   \n",
       "117  2018-04-18 00:00:00  600100  10.74    1000     962.2925  Order_fR1zVgNU   \n",
       "118  2018-04-20 00:00:00  300051  11.29   -1000   12272.0500  Order_7g6uwcl4   \n",
       "119  2018-04-20 00:00:00  600589   5.47    1000    6792.4775  Order_p5UcQmBw   \n",
       "120  2018-04-20 00:00:00  600590  11.29   -1000   18102.2350  Order_img5TnKy   \n",
       "121  2018-04-20 00:00:00  600601   3.09    1000   15006.8275  Order_dI9SJy3q   \n",
       "122  2018-04-23 00:00:00  300366  12.45    1000    2535.0400  Order_k2rIMafR   \n",
       "123  2018-04-23 00:00:00  600601   3.08   -1000    5620.4300  Order_dtTBM43Y   \n",
       "124  2018-04-24 00:00:00  600601   3.08    1000    2535.0400  Order_xrFNEVC4   \n",
       "125  2018-04-25 00:00:00  600845  30.00   -1000   32587.5400  Order_qm1vYekP   \n",
       "126  2018-04-26 00:00:00  000066   9.28   -1000   41883.7800  Order_Q5H2Fkrm   \n",
       "127  2018-04-26 00:00:00  000611   7.56    1000   34310.5500  Order_5vLmotrf   \n",
       "128  2018-04-26 00:00:00  000836   4.56    1000   29742.5700  Order_8c0vIeK3   \n",
       "129  2018-04-26 00:00:00  002063  11.72    1000   18002.0600  Order_v26iRnZQ   \n",
       "130  2018-04-26 00:00:00  300025   5.07    1000   12923.1875  Order_U1mKR6OG   \n",
       "131  2018-04-26 00:00:00  300235  12.37    1000     531.5400  Order_8HUWfJx1   \n",
       "132  2018-04-27 00:00:00  002063  11.64   -1000   12191.9100  Order_BtPZvUWw   \n",
       "133  2018-04-27 00:00:00  601360  37.80   -1000   50058.0600  Order_lyDrw7iT   \n",
       "\n",
       "       realorder_id        trade_id account_cookie  commission     tax  \n",
       "0    Order_AGZefuXd  Trade_7RxnPTq1   JCSC_EXAMPLE      1.4775   8.865  \n",
       "1    Order_qOuEB4fo  Trade_5IZEW2LB   JCSC_EXAMPLE      5.1950  31.170  \n",
       "2    Order_ripYwt6L  Trade_VzvpFjPM   JCSC_EXAMPLE      3.9625  23.775  \n",
       "3    Order_ph50Tje9  Trade_vWYaMmhq   JCSC_EXAMPLE      2.1775  13.065  \n",
       "4    Order_YvlByWfD  Trade_zWlyg0UM   JCSC_EXAMPLE      3.8475  23.085  \n",
       "5    Order_8sBTIvLO  Trade_cay7rZ6J   JCSC_EXAMPLE      1.6450   9.870  \n",
       "6    Order_whQIWHBi  Trade_NtWVGFSo   JCSC_EXAMPLE      2.9675  17.805  \n",
       "7    Order_wDPTJiRh  Trade_eufovKcX   JCSC_EXAMPLE      2.3800  14.280  \n",
       "8    Order_f8yNTPHe  Trade_OUEDoFnu   JCSC_EXAMPLE      0.9975   5.985  \n",
       "9    Order_x5k8PvbA  Trade_dBbge5v4   JCSC_EXAMPLE      2.1325  12.795  \n",
       "10   Order_jKYkEcmX  Trade_L1dMti6K   JCSC_EXAMPLE      7.5100  45.060  \n",
       "11   Order_iB3KzEPv  Trade_rXCb1PJu   JCSC_EXAMPLE      3.9450  23.670  \n",
       "12   Order_eFZH05bs  Trade_nHqFwT30   JCSC_EXAMPLE      2.9125  17.475  \n",
       "13   Order_K3MjyXZo  Trade_zrGbK97E   JCSC_EXAMPLE      3.7500  22.500  \n",
       "14   Order_EdD6u1Cb  Trade_Bw0n39H5   JCSC_EXAMPLE      4.4825  26.895  \n",
       "15   Order_KYdA3NQ9  Trade_rf1oEbiF   JCSC_EXAMPLE     -3.7275 -22.365  \n",
       "16   Order_uCE5pWke  Trade_ZGCEmfb8   JCSC_EXAMPLE      3.4500  20.700  \n",
       "17   Order_p5J1Paxo  Trade_1quYOxnZ   JCSC_EXAMPLE     -4.9600 -29.760  \n",
       "18   Order_GOfSMKya  Trade_PIZ23WAV   JCSC_EXAMPLE      3.9625  23.775  \n",
       "19   Order_kK1V8DEQ  Trade_3Cq2vZib   JCSC_EXAMPLE     -3.6225 -21.735  \n",
       "20   Order_qcGuE2ij  Trade_ubTdkr14   JCSC_EXAMPLE     -3.3450 -20.070  \n",
       "21   Order_XAcLutCp  Trade_OjA3lpNn   JCSC_EXAMPLE     -2.0200 -12.120  \n",
       "22   Order_VXd1B3KE  Trade_KqQpcCGy   JCSC_EXAMPLE     -2.6525 -15.915  \n",
       "23   Order_xfhHbnI0  Trade_2ctPwXGN   JCSC_EXAMPLE      9.6500  57.900  \n",
       "24   Order_ydeshXSg  Trade_JgWf6d1e   JCSC_EXAMPLE     -3.6550 -21.930  \n",
       "25   Order_tWCmXwzc  Trade_0jDlCpSA   JCSC_EXAMPLE     -3.5675 -21.405  \n",
       "26   Order_tZncUvNb  Trade_ChUqo3HI   JCSC_EXAMPLE     -4.1275 -24.765  \n",
       "27   Order_X3FLjoUW  Trade_qtGE2dYw   JCSC_EXAMPLE      2.3900  14.340  \n",
       "28   Order_gwUSRf3G  Trade_jTevtxld   JCSC_EXAMPLE     -9.2150 -55.290  \n",
       "29   Order_nuivkPTW  Trade_PKRkTfIc   JCSC_EXAMPLE      2.5825  15.495  \n",
       "..              ...             ...            ...         ...     ...  \n",
       "104  Order_pjNsHFm5  Trade_KdhnNHOe   JCSC_EXAMPLE      2.0800  12.480  \n",
       "105  Order_g3w6Eir7  Trade_j2tT6B3x   JCSC_EXAMPLE     -4.0850 -24.510  \n",
       "106  Order_vi4usBEU  Trade_8NPLyuqB   JCSC_EXAMPLE      2.4500  14.700  \n",
       "107  Order_avKOAeWI  Trade_UvTz98l6   JCSC_EXAMPLE     -4.4375 -26.625  \n",
       "108  Order_kLGItRjr  Trade_XwPiIrMC   JCSC_EXAMPLE      1.3675   8.205  \n",
       "109  Order_E2Vx6M3o  Trade_IuTMkVep   JCSC_EXAMPLE      3.0275  18.165  \n",
       "110  Order_XLp31JS6  Trade_R87jVyex   JCSC_EXAMPLE     -1.8175 -10.905  \n",
       "111  Order_ubHjJ3Tr  Trade_jTY5sS7D   JCSC_EXAMPLE      2.1000  12.600  \n",
       "112  Order_myObDLoh  Trade_ds7iXu4V   JCSC_EXAMPLE     -2.3900 -14.340  \n",
       "113  Order_fzOQt846  Trade_DQlIEonw   JCSC_EXAMPLE     -1.3425  -8.055  \n",
       "114  Order_Ae5XduIP  Trade_amJjUL0o   JCSC_EXAMPLE     -1.7800 -10.680  \n",
       "115  Order_X7xe5kOH  Trade_TVimMICX   JCSC_EXAMPLE      1.0875   6.525  \n",
       "116  Order_pcYyubnM  Trade_R1KrCWaw   JCSC_EXAMPLE      3.0000  18.000  \n",
       "117  Order_fR1zVgNU  Trade_cj2bPWtZ   JCSC_EXAMPLE      2.6850  16.110  \n",
       "118  Order_7g6uwcl4  Trade_OaPhtvDf   JCSC_EXAMPLE     -2.8225 -16.935  \n",
       "119  Order_p5UcQmBw  Trade_6fkmJV4P   JCSC_EXAMPLE      1.3675   8.205  \n",
       "120  Order_img5TnKy  Trade_fjUkgyIM   JCSC_EXAMPLE     -2.8225 -16.935  \n",
       "121  Order_dI9SJy3q  Trade_S7k6KvgN   JCSC_EXAMPLE      0.7725   4.635  \n",
       "122  Order_k2rIMafR  Trade_NVH6ZrhU   JCSC_EXAMPLE      3.1125  18.675  \n",
       "123  Order_dtTBM43Y  Trade_VchbZSEH   JCSC_EXAMPLE     -0.7700  -4.620  \n",
       "124  Order_xrFNEVC4  Trade_BlUXpNAc   JCSC_EXAMPLE      0.7700   4.620  \n",
       "125  Order_qm1vYekP  Trade_Z8PMI0wO   JCSC_EXAMPLE     -7.5000 -45.000  \n",
       "126  Order_Q5H2Fkrm  Trade_5kSnPrJ0   JCSC_EXAMPLE     -2.3200 -13.920  \n",
       "127  Order_5vLmotrf  Trade_9aXfk1ur   JCSC_EXAMPLE      1.8900  11.340  \n",
       "128  Order_8c0vIeK3  Trade_aez4PKrt   JCSC_EXAMPLE      1.1400   6.840  \n",
       "129  Order_v26iRnZQ  Trade_CtKujRbr   JCSC_EXAMPLE      2.9300  17.580  \n",
       "130  Order_U1mKR6OG  Trade_18JMpRnG   JCSC_EXAMPLE      1.2675   7.605  \n",
       "131  Order_8HUWfJx1  Trade_WPNlvA1E   JCSC_EXAMPLE      3.0925  18.555  \n",
       "132  Order_BtPZvUWw  Trade_ICkVoQOZ   JCSC_EXAMPLE     -2.9100 -17.460  \n",
       "133  Order_lyDrw7iT  Trade_3aozRWnk   JCSC_EXAMPLE     -9.4500 -56.700  \n",
       "\n",
       "[134 rows x 11 columns]"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Account.history_table"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>cash</th>\n",
       "      <th>datetime</th>\n",
       "      <th>date</th>\n",
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       "      <th rowspan=\"7\" valign=\"top\">2018-01-02 00:00:00</th>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
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       "      <td>2018-01-02 00:00:00</td>\n",
       "      <td>2018-01-02</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
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       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>173263</td>\n",
       "      <td>2018-01-02 00:00:00</td>\n",
       "      <td>2018-01-02</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
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       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>157386</td>\n",
       "      <td>2018-01-02 00:00:00</td>\n",
       "      <td>2018-01-02</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>148660</td>\n",
       "      <td>2018-01-02 00:00:00</td>\n",
       "      <td>2018-01-02</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
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       "    <tr>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>133243</td>\n",
       "      <td>2018-01-02 00:00:00</td>\n",
       "      <td>2018-01-02</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>126652</td>\n",
       "      <td>2018-01-02 00:00:00</td>\n",
       "      <td>2018-01-02</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>114761</td>\n",
       "      <td>2018-01-02 00:00:00</td>\n",
       "      <td>2018-01-02</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"8\" valign=\"top\">2018-01-03 00:00:00</th>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>105224</td>\n",
       "      <td>2018-01-03 00:00:00</td>\n",
       "      <td>2018-01-03</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>101227</td>\n",
       "      <td>2018-01-03 00:00:00</td>\n",
       "      <td>2018-01-03</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>92682.5</td>\n",
       "      <td>2018-01-03 00:00:00</td>\n",
       "      <td>2018-01-03</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>62590</td>\n",
       "      <td>2018-01-03 00:00:00</td>\n",
       "      <td>2018-01-03</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>46782.3</td>\n",
       "      <td>2018-01-03 00:00:00</td>\n",
       "      <td>2018-01-03</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>35112</td>\n",
       "      <td>2018-01-03 00:00:00</td>\n",
       "      <td>2018-01-03</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>20085.7</td>\n",
       "      <td>2018-01-03 00:00:00</td>\n",
       "      <td>2018-01-03</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>2124.32</td>\n",
       "      <td>2018-01-03 00:00:00</td>\n",
       "      <td>2018-01-03</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-09 00:00:00</th>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>17060.4</td>\n",
       "      <td>2018-01-09 00:00:00</td>\n",
       "      <td>2018-01-09</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-10 00:00:00</th>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>3236.27</td>\n",
       "      <td>2018-01-10 00:00:00</td>\n",
       "      <td>2018-01-10</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
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       "      <th rowspan=\"2\" valign=\"top\">2018-01-12 00:00:00</th>\n",
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       "      <td>2018-01-12 00:00:00</td>\n",
       "      <td>2018-01-12</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>7233.25</td>\n",
       "      <td>2018-01-12 00:00:00</td>\n",
       "      <td>2018-01-12</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
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       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">2018-01-15 00:00:00</th>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>21748.6</td>\n",
       "      <td>2018-01-15 00:00:00</td>\n",
       "      <td>2018-01-15</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>35152</td>\n",
       "      <td>2018-01-15 00:00:00</td>\n",
       "      <td>2018-01-15</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>43246.2</td>\n",
       "      <td>2018-01-15 00:00:00</td>\n",
       "      <td>2018-01-15</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>53874.7</td>\n",
       "      <td>2018-01-15 00:00:00</td>\n",
       "      <td>2018-01-15</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">2018-01-16 00:00:00</th>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>15207.2</td>\n",
       "      <td>2018-01-16 00:00:00</td>\n",
       "      <td>2018-01-16</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>29852.8</td>\n",
       "      <td>2018-01-16 00:00:00</td>\n",
       "      <td>2018-01-16</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>44147.7</td>\n",
       "      <td>2018-01-16 00:00:00</td>\n",
       "      <td>2018-01-16</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>60686.6</td>\n",
       "      <td>2018-01-16 00:00:00</td>\n",
       "      <td>2018-01-16</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-17 00:00:00</th>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>51109.9</td>\n",
       "      <td>2018-01-17 00:00:00</td>\n",
       "      <td>2018-01-17</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">2018-01-19 00:00:00</th>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>88034.4</td>\n",
       "      <td>2018-01-19 00:00:00</td>\n",
       "      <td>2018-01-19</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>77686.3</td>\n",
       "      <td>2018-01-19 00:00:00</td>\n",
       "      <td>2018-01-19</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-04-12 00:00:00</th>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>421.348</td>\n",
       "      <td>2018-04-12 00:00:00</td>\n",
       "      <td>2018-04-12</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"6\" valign=\"top\">2018-04-13 00:00:00</th>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>16789.9</td>\n",
       "      <td>2018-04-13 00:00:00</td>\n",
       "      <td>2018-04-13</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>6972.79</td>\n",
       "      <td>2018-04-13 00:00:00</td>\n",
       "      <td>2018-04-13</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>24753.9</td>\n",
       "      <td>2018-04-13 00:00:00</td>\n",
       "      <td>2018-04-13</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>19274.3</td>\n",
       "      <td>2018-04-13 00:00:00</td>\n",
       "      <td>2018-04-13</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>7143.09</td>\n",
       "      <td>2018-04-13 00:00:00</td>\n",
       "      <td>2018-04-13</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>14425.8</td>\n",
       "      <td>2018-04-13 00:00:00</td>\n",
       "      <td>2018-04-13</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-04-16 00:00:00</th>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>6011.11</td>\n",
       "      <td>2018-04-16 00:00:00</td>\n",
       "      <td>2018-04-16</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">2018-04-17 00:00:00</th>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>15587.8</td>\n",
       "      <td>2018-04-17 00:00:00</td>\n",
       "      <td>2018-04-17</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>20967.2</td>\n",
       "      <td>2018-04-17 00:00:00</td>\n",
       "      <td>2018-04-17</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>28099.7</td>\n",
       "      <td>2018-04-17 00:00:00</td>\n",
       "      <td>2018-04-17</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">2018-04-18 00:00:00</th>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>23742.1</td>\n",
       "      <td>2018-04-18 00:00:00</td>\n",
       "      <td>2018-04-18</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>11721.1</td>\n",
       "      <td>2018-04-18 00:00:00</td>\n",
       "      <td>2018-04-18</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>962.293</td>\n",
       "      <td>2018-04-18 00:00:00</td>\n",
       "      <td>2018-04-18</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">2018-04-20 00:00:00</th>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>12272.1</td>\n",
       "      <td>2018-04-20 00:00:00</td>\n",
       "      <td>2018-04-20</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>6792.48</td>\n",
       "      <td>2018-04-20 00:00:00</td>\n",
       "      <td>2018-04-20</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>18102.2</td>\n",
       "      <td>2018-04-20 00:00:00</td>\n",
       "      <td>2018-04-20</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>15006.8</td>\n",
       "      <td>2018-04-20 00:00:00</td>\n",
       "      <td>2018-04-20</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">2018-04-23 00:00:00</th>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>2535.04</td>\n",
       "      <td>2018-04-23 00:00:00</td>\n",
       "      <td>2018-04-23</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>5620.43</td>\n",
       "      <td>2018-04-23 00:00:00</td>\n",
       "      <td>2018-04-23</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-04-24 00:00:00</th>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>2535.04</td>\n",
       "      <td>2018-04-24 00:00:00</td>\n",
       "      <td>2018-04-24</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-04-25 00:00:00</th>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>32587.5</td>\n",
       "      <td>2018-04-25 00:00:00</td>\n",
       "      <td>2018-04-25</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"6\" valign=\"top\">2018-04-26 00:00:00</th>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>41883.8</td>\n",
       "      <td>2018-04-26 00:00:00</td>\n",
       "      <td>2018-04-26</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>34310.6</td>\n",
       "      <td>2018-04-26 00:00:00</td>\n",
       "      <td>2018-04-26</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>29742.6</td>\n",
       "      <td>2018-04-26 00:00:00</td>\n",
       "      <td>2018-04-26</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>18002.1</td>\n",
       "      <td>2018-04-26 00:00:00</td>\n",
       "      <td>2018-04-26</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>12923.2</td>\n",
       "      <td>2018-04-26 00:00:00</td>\n",
       "      <td>2018-04-26</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>531.54</td>\n",
       "      <td>2018-04-26 00:00:00</td>\n",
       "      <td>2018-04-26</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">2018-04-27 00:00:00</th>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>12191.9</td>\n",
       "      <td>2018-04-27 00:00:00</td>\n",
       "      <td>2018-04-27</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JCSC_EXAMPLE</th>\n",
       "      <td>50058.1</td>\n",
       "      <td>2018-04-27 00:00:00</td>\n",
       "      <td>2018-04-27</td>\n",
       "      <td>JCSC_EXAMPLE</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>134 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                       cash             datetime       date  \\\n",
       "datetime            account_cookie                                            \n",
       "2018-01-02 00:00:00 JCSC_EXAMPLE     194080  2018-01-02 00:00:00 2018-01-02   \n",
       "                    JCSC_EXAMPLE     173263  2018-01-02 00:00:00 2018-01-02   \n",
       "                    JCSC_EXAMPLE     157386  2018-01-02 00:00:00 2018-01-02   \n",
       "                    JCSC_EXAMPLE     148660  2018-01-02 00:00:00 2018-01-02   \n",
       "                    JCSC_EXAMPLE     133243  2018-01-02 00:00:00 2018-01-02   \n",
       "                    JCSC_EXAMPLE     126652  2018-01-02 00:00:00 2018-01-02   \n",
       "                    JCSC_EXAMPLE     114761  2018-01-02 00:00:00 2018-01-02   \n",
       "2018-01-03 00:00:00 JCSC_EXAMPLE     105224  2018-01-03 00:00:00 2018-01-03   \n",
       "                    JCSC_EXAMPLE     101227  2018-01-03 00:00:00 2018-01-03   \n",
       "                    JCSC_EXAMPLE    92682.5  2018-01-03 00:00:00 2018-01-03   \n",
       "                    JCSC_EXAMPLE      62590  2018-01-03 00:00:00 2018-01-03   \n",
       "                    JCSC_EXAMPLE    46782.3  2018-01-03 00:00:00 2018-01-03   \n",
       "                    JCSC_EXAMPLE      35112  2018-01-03 00:00:00 2018-01-03   \n",
       "                    JCSC_EXAMPLE    20085.7  2018-01-03 00:00:00 2018-01-03   \n",
       "                    JCSC_EXAMPLE    2124.32  2018-01-03 00:00:00 2018-01-03   \n",
       "2018-01-09 00:00:00 JCSC_EXAMPLE    17060.4  2018-01-09 00:00:00 2018-01-09   \n",
       "2018-01-10 00:00:00 JCSC_EXAMPLE    3236.27  2018-01-10 00:00:00 2018-01-10   \n",
       "2018-01-12 00:00:00 JCSC_EXAMPLE      23111  2018-01-12 00:00:00 2018-01-12   \n",
       "                    JCSC_EXAMPLE    7233.25  2018-01-12 00:00:00 2018-01-12   \n",
       "2018-01-15 00:00:00 JCSC_EXAMPLE    21748.6  2018-01-15 00:00:00 2018-01-15   \n",
       "                    JCSC_EXAMPLE      35152  2018-01-15 00:00:00 2018-01-15   \n",
       "                    JCSC_EXAMPLE    43246.2  2018-01-15 00:00:00 2018-01-15   \n",
       "                    JCSC_EXAMPLE    53874.7  2018-01-15 00:00:00 2018-01-15   \n",
       "2018-01-16 00:00:00 JCSC_EXAMPLE    15207.2  2018-01-16 00:00:00 2018-01-16   \n",
       "                    JCSC_EXAMPLE    29852.8  2018-01-16 00:00:00 2018-01-16   \n",
       "                    JCSC_EXAMPLE    44147.7  2018-01-16 00:00:00 2018-01-16   \n",
       "                    JCSC_EXAMPLE    60686.6  2018-01-16 00:00:00 2018-01-16   \n",
       "2018-01-17 00:00:00 JCSC_EXAMPLE    51109.9  2018-01-17 00:00:00 2018-01-17   \n",
       "2018-01-19 00:00:00 JCSC_EXAMPLE    88034.4  2018-01-19 00:00:00 2018-01-19   \n",
       "                    JCSC_EXAMPLE    77686.3  2018-01-19 00:00:00 2018-01-19   \n",
       "...                                     ...                  ...        ...   \n",
       "2018-04-12 00:00:00 JCSC_EXAMPLE    421.348  2018-04-12 00:00:00 2018-04-12   \n",
       "2018-04-13 00:00:00 JCSC_EXAMPLE    16789.9  2018-04-13 00:00:00 2018-04-13   \n",
       "                    JCSC_EXAMPLE    6972.79  2018-04-13 00:00:00 2018-04-13   \n",
       "                    JCSC_EXAMPLE    24753.9  2018-04-13 00:00:00 2018-04-13   \n",
       "                    JCSC_EXAMPLE    19274.3  2018-04-13 00:00:00 2018-04-13   \n",
       "                    JCSC_EXAMPLE    7143.09  2018-04-13 00:00:00 2018-04-13   \n",
       "                    JCSC_EXAMPLE    14425.8  2018-04-13 00:00:00 2018-04-13   \n",
       "2018-04-16 00:00:00 JCSC_EXAMPLE    6011.11  2018-04-16 00:00:00 2018-04-16   \n",
       "2018-04-17 00:00:00 JCSC_EXAMPLE    15587.8  2018-04-17 00:00:00 2018-04-17   \n",
       "                    JCSC_EXAMPLE    20967.2  2018-04-17 00:00:00 2018-04-17   \n",
       "                    JCSC_EXAMPLE    28099.7  2018-04-17 00:00:00 2018-04-17   \n",
       "2018-04-18 00:00:00 JCSC_EXAMPLE    23742.1  2018-04-18 00:00:00 2018-04-18   \n",
       "                    JCSC_EXAMPLE    11721.1  2018-04-18 00:00:00 2018-04-18   \n",
       "                    JCSC_EXAMPLE    962.293  2018-04-18 00:00:00 2018-04-18   \n",
       "2018-04-20 00:00:00 JCSC_EXAMPLE    12272.1  2018-04-20 00:00:00 2018-04-20   \n",
       "                    JCSC_EXAMPLE    6792.48  2018-04-20 00:00:00 2018-04-20   \n",
       "                    JCSC_EXAMPLE    18102.2  2018-04-20 00:00:00 2018-04-20   \n",
       "                    JCSC_EXAMPLE    15006.8  2018-04-20 00:00:00 2018-04-20   \n",
       "2018-04-23 00:00:00 JCSC_EXAMPLE    2535.04  2018-04-23 00:00:00 2018-04-23   \n",
       "                    JCSC_EXAMPLE    5620.43  2018-04-23 00:00:00 2018-04-23   \n",
       "2018-04-24 00:00:00 JCSC_EXAMPLE    2535.04  2018-04-24 00:00:00 2018-04-24   \n",
       "2018-04-25 00:00:00 JCSC_EXAMPLE    32587.5  2018-04-25 00:00:00 2018-04-25   \n",
       "2018-04-26 00:00:00 JCSC_EXAMPLE    41883.8  2018-04-26 00:00:00 2018-04-26   \n",
       "                    JCSC_EXAMPLE    34310.6  2018-04-26 00:00:00 2018-04-26   \n",
       "                    JCSC_EXAMPLE    29742.6  2018-04-26 00:00:00 2018-04-26   \n",
       "                    JCSC_EXAMPLE    18002.1  2018-04-26 00:00:00 2018-04-26   \n",
       "                    JCSC_EXAMPLE    12923.2  2018-04-26 00:00:00 2018-04-26   \n",
       "                    JCSC_EXAMPLE     531.54  2018-04-26 00:00:00 2018-04-26   \n",
       "2018-04-27 00:00:00 JCSC_EXAMPLE    12191.9  2018-04-27 00:00:00 2018-04-27   \n",
       "                    JCSC_EXAMPLE    50058.1  2018-04-27 00:00:00 2018-04-27   \n",
       "\n",
       "                                   account_cookie  \n",
       "datetime            account_cookie                 \n",
       "2018-01-02 00:00:00 JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "                    JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "                    JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "                    JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "                    JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "                    JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "                    JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "2018-01-03 00:00:00 JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "                    JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "                    JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "                    JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "                    JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "                    JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "                    JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "                    JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "2018-01-09 00:00:00 JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "2018-01-10 00:00:00 JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "2018-01-12 00:00:00 JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "                    JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "2018-01-15 00:00:00 JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "                    JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "                    JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "                    JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "2018-01-16 00:00:00 JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "                    JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "                    JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "                    JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "2018-01-17 00:00:00 JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "2018-01-19 00:00:00 JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "                    JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "...                                           ...  \n",
       "2018-04-12 00:00:00 JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "2018-04-13 00:00:00 JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "                    JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "                    JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "                    JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "                    JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "                    JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "2018-04-16 00:00:00 JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "2018-04-17 00:00:00 JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "                    JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "                    JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "2018-04-18 00:00:00 JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "                    JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "                    JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "2018-04-20 00:00:00 JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "                    JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "                    JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "                    JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "2018-04-23 00:00:00 JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "                    JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "2018-04-24 00:00:00 JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "2018-04-25 00:00:00 JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "2018-04-26 00:00:00 JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "                    JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "                    JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "                    JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "                    JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "                    JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "2018-04-27 00:00:00 JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "                    JCSC_EXAMPLE     JCSC_EXAMPLE  \n",
       "\n",
       "[134 rows x 4 columns]"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Account.cash_table"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "date\n",
       "2018-01-02    199851.092500\n",
       "2018-01-03    202044.322500\n",
       "2018-01-09    198830.415000\n",
       "2018-01-10    198426.265000\n",
       "2018-01-12    199443.247500\n",
       "2018-01-15    194514.727500\n",
       "2018-01-16    195436.627500\n",
       "2018-01-17    190949.897500\n",
       "2018-01-19    190333.135000\n",
       "2018-01-22    199560.342500\n",
       "2018-01-23    198321.517500\n",
       "2018-01-24    206019.747500\n",
       "2018-01-25    203280.962500\n",
       "2018-01-29    202659.555000\n",
       "2018-01-31    194866.850000\n",
       "2018-02-01    191795.377500\n",
       "2018-02-02    192775.562500\n",
       "2018-02-06    191412.685000\n",
       "2018-02-07    197642.810774\n",
       "2018-02-08    199346.296242\n",
       "2018-02-12    194668.988401\n",
       "2018-02-22    209311.818521\n",
       "2018-03-02    207590.834105\n",
       "2018-03-07    208910.506605\n",
       "2018-03-09    213890.688775\n",
       "2018-03-12    216488.311504\n",
       "2018-03-14    207859.383873\n",
       "2018-03-16    199776.050000\n",
       "2018-03-19    200788.742500\n",
       "2018-03-20    201404.090047\n",
       "2018-03-21    201870.022620\n",
       "2018-03-22    202142.294610\n",
       "2018-03-23    193589.271814\n",
       "2018-03-26    195724.343417\n",
       "2018-03-27    200889.965918\n",
       "2018-04-04    197286.460121\n",
       "2018-04-09    199386.650187\n",
       "2018-04-10    192295.974214\n",
       "2018-04-11    192331.617057\n",
       "2018-04-12    190417.369344\n",
       "2018-04-13    191885.812500\n",
       "2018-04-16    195351.112500\n",
       "2018-04-17    192959.700000\n",
       "2018-04-18    199342.292500\n",
       "2018-04-20    196366.827500\n",
       "2018-04-23    190870.430000\n",
       "2018-04-24    195945.040000\n",
       "2018-04-25    196617.540000\n",
       "2018-04-26    192751.540000\n",
       "2018-04-27    190028.060000\n",
       "Name: 0, dtype: float64"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Risk.assets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1eb5090b5f8>"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "Risk.assets.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1eb50b0bd30>"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "Risk.benchmark_assets.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<module 'matplotlib.pyplot' from 'C:\\\\ProgramData\\\\Anaconda3\\\\lib\\\\site-packages\\\\matplotlib\\\\pyplot.py'>"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x864 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "Risk.plot_assets_curve()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<module 'matplotlib.pyplot' from 'C:\\\\ProgramData\\\\Anaconda3\\\\lib\\\\site-packages\\\\matplotlib\\\\pyplot.py'>"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x576 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "Risk.plot_dailyhold()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<module 'matplotlib.pyplot' from 'C:\\\\ProgramData\\\\Anaconda3\\\\lib\\\\site-packages\\\\matplotlib\\\\pyplot.py'>"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x1296 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "Risk.plot_signal()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'total_buyandsell': -9710.0,\n",
       " 'total_tax': -224.52,\n",
       " 'total_commission': -37.42,\n",
       " 'total_profit': -9971.94}"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Risk.profit_construct"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "Performance=QA.QA_Performance(Account)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>sell_date</th>\n",
       "      <th>buy_date</th>\n",
       "      <th>amount</th>\n",
       "      <th>sell_price</th>\n",
       "      <th>buy_price</th>\n",
       "      <th>pnl_ratio</th>\n",
       "      <th>pnl_money</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>code</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>300367</th>\n",
       "      <td>2018-01-09</td>\n",
       "      <td>2018-01-02</td>\n",
       "      <td>1000</td>\n",
       "      <td>14.91</td>\n",
       "      <td>15.39</td>\n",
       "      <td>-0.031189</td>\n",
       "      <td>-480.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>002456</th>\n",
       "      <td>2018-01-12</td>\n",
       "      <td>2018-01-02</td>\n",
       "      <td>1000</td>\n",
       "      <td>19.84</td>\n",
       "      <td>20.78</td>\n",
       "      <td>-0.045236</td>\n",
       "      <td>-940.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>300036</th>\n",
       "      <td>2018-01-15</td>\n",
       "      <td>2018-01-03</td>\n",
       "      <td>1000</td>\n",
       "      <td>14.49</td>\n",
       "      <td>15.78</td>\n",
       "      <td>-0.081749</td>\n",
       "      <td>-1290.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>300245</th>\n",
       "      <td>2018-01-15</td>\n",
       "      <td>2018-01-10</td>\n",
       "      <td>1000</td>\n",
       "      <td>13.38</td>\n",
       "      <td>13.80</td>\n",
       "      <td>-0.030435</td>\n",
       "      <td>-420.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>300290</th>\n",
       "      <td>2018-01-15</td>\n",
       "      <td>2018-01-02</td>\n",
       "      <td>1000</td>\n",
       "      <td>8.08</td>\n",
       "      <td>8.71</td>\n",
       "      <td>-0.072331</td>\n",
       "      <td>-630.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>600198</th>\n",
       "      <td>2018-01-15</td>\n",
       "      <td>2018-01-03</td>\n",
       "      <td>1000</td>\n",
       "      <td>10.61</td>\n",
       "      <td>11.65</td>\n",
       "      <td>-0.089270</td>\n",
       "      <td>-1040.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>002544</th>\n",
       "      <td>2018-01-16</td>\n",
       "      <td>2018-01-02</td>\n",
       "      <td>1000</td>\n",
       "      <td>14.62</td>\n",
       "      <td>15.85</td>\n",
       "      <td>-0.077603</td>\n",
       "      <td>-1230.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>600718</th>\n",
       "      <td>2018-01-16</td>\n",
       "      <td>2018-01-03</td>\n",
       "      <td>1000</td>\n",
       "      <td>14.27</td>\n",
       "      <td>15.00</td>\n",
       "      <td>-0.048667</td>\n",
       "      <td>-730.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>600804</th>\n",
       "      <td>2018-01-16</td>\n",
       "      <td>2018-01-03</td>\n",
       "      <td>1000</td>\n",
       "      <td>16.51</td>\n",
       "      <td>17.93</td>\n",
       "      <td>-0.079197</td>\n",
       "      <td>-1420.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>000063</th>\n",
       "      <td>2018-01-19</td>\n",
       "      <td>2018-01-16</td>\n",
       "      <td>1000</td>\n",
       "      <td>36.86</td>\n",
       "      <td>38.60</td>\n",
       "      <td>-0.045078</td>\n",
       "      <td>-1740.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>000100</th>\n",
       "      <td>2018-01-23</td>\n",
       "      <td>2018-01-03</td>\n",
       "      <td>1000</td>\n",
       "      <td>3.85</td>\n",
       "      <td>3.99</td>\n",
       "      <td>-0.035088</td>\n",
       "      <td>-140.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>300052</th>\n",
       "      <td>2018-01-23</td>\n",
       "      <td>2018-01-12</td>\n",
       "      <td>1000</td>\n",
       "      <td>14.38</td>\n",
       "      <td>15.85</td>\n",
       "      <td>-0.092744</td>\n",
       "      <td>-1470.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>600797</th>\n",
       "      <td>2018-01-23</td>\n",
       "      <td>2018-01-02</td>\n",
       "      <td>1000</td>\n",
       "      <td>12.25</td>\n",
       "      <td>11.87</td>\n",
       "      <td>0.032013</td>\n",
       "      <td>380.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>600225</th>\n",
       "      <td>2018-01-29</td>\n",
       "      <td>2018-01-25</td>\n",
       "      <td>1000</td>\n",
       "      <td>4.91</td>\n",
       "      <td>5.02</td>\n",
       "      <td>-0.021912</td>\n",
       "      <td>-110.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>000070</th>\n",
       "      <td>2018-01-31</td>\n",
       "      <td>2018-01-03</td>\n",
       "      <td>1000</td>\n",
       "      <td>9.45</td>\n",
       "      <td>9.52</td>\n",
       "      <td>-0.007353</td>\n",
       "      <td>-70.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>002065</th>\n",
       "      <td>2018-01-31</td>\n",
       "      <td>2018-01-03</td>\n",
       "      <td>1000</td>\n",
       "      <td>7.99</td>\n",
       "      <td>8.53</td>\n",
       "      <td>-0.063306</td>\n",
       "      <td>-540.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>002195</th>\n",
       "      <td>2018-01-31</td>\n",
       "      <td>2018-01-02</td>\n",
       "      <td>1000</td>\n",
       "      <td>6.16</td>\n",
       "      <td>5.91</td>\n",
       "      <td>0.042301</td>\n",
       "      <td>250.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>002335</th>\n",
       "      <td>2018-01-31</td>\n",
       "      <td>2018-01-03</td>\n",
       "      <td>1000</td>\n",
       "      <td>28.81</td>\n",
       "      <td>30.04</td>\n",
       "      <td>-0.040945</td>\n",
       "      <td>-1230.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>000066</th>\n",
       "      <td>2018-02-01</td>\n",
       "      <td>2018-01-24</td>\n",
       "      <td>1000</td>\n",
       "      <td>6.90</td>\n",
       "      <td>7.16</td>\n",
       "      <td>-0.036313</td>\n",
       "      <td>-260.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>002279</th>\n",
       "      <td>2018-02-01</td>\n",
       "      <td>2018-01-19</td>\n",
       "      <td>1000</td>\n",
       "      <td>10.25</td>\n",
       "      <td>10.33</td>\n",
       "      <td>-0.007744</td>\n",
       "      <td>-80.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>002396</th>\n",
       "      <td>2018-02-01</td>\n",
       "      <td>2018-01-31</td>\n",
       "      <td>1000</td>\n",
       "      <td>19.21</td>\n",
       "      <td>19.67</td>\n",
       "      <td>-0.023386</td>\n",
       "      <td>-460.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>300297</th>\n",
       "      <td>2018-02-01</td>\n",
       "      <td>2018-01-17</td>\n",
       "      <td>1000</td>\n",
       "      <td>9.22</td>\n",
       "      <td>9.56</td>\n",
       "      <td>-0.035565</td>\n",
       "      <td>-340.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>600105</th>\n",
       "      <td>2018-02-01</td>\n",
       "      <td>2018-01-02</td>\n",
       "      <td>1000</td>\n",
       "      <td>6.15</td>\n",
       "      <td>6.58</td>\n",
       "      <td>-0.065350</td>\n",
       "      <td>-430.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>600804</th>\n",
       "      <td>2018-02-01</td>\n",
       "      <td>2018-01-19</td>\n",
       "      <td>1000</td>\n",
       "      <td>16.00</td>\n",
       "      <td>17.22</td>\n",
       "      <td>-0.070848</td>\n",
       "      <td>-1220.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>000836</th>\n",
       "      <td>2018-02-06</td>\n",
       "      <td>2018-01-24</td>\n",
       "      <td>1000</td>\n",
       "      <td>4.98</td>\n",
       "      <td>5.28</td>\n",
       "      <td>-0.056818</td>\n",
       "      <td>-300.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>002095</th>\n",
       "      <td>2018-02-06</td>\n",
       "      <td>2018-01-22</td>\n",
       "      <td>1000</td>\n",
       "      <td>39.09</td>\n",
       "      <td>38.61</td>\n",
       "      <td>0.012432</td>\n",
       "      <td>480.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>601360</th>\n",
       "      <td>2018-03-02</td>\n",
       "      <td>2018-02-02</td>\n",
       "      <td>1000</td>\n",
       "      <td>52.51</td>\n",
       "      <td>55.03</td>\n",
       "      <td>-0.045793</td>\n",
       "      <td>-2520.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>300113</th>\n",
       "      <td>2018-03-07</td>\n",
       "      <td>2018-01-23</td>\n",
       "      <td>1000</td>\n",
       "      <td>22.67</td>\n",
       "      <td>18.38</td>\n",
       "      <td>0.233406</td>\n",
       "      <td>4290.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>300113</th>\n",
       "      <td>2018-03-14</td>\n",
       "      <td>2018-03-12</td>\n",
       "      <td>1000</td>\n",
       "      <td>23.70</td>\n",
       "      <td>24.08</td>\n",
       "      <td>-0.015781</td>\n",
       "      <td>-380.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>300212</th>\n",
       "      <td>2018-03-14</td>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>1000</td>\n",
       "      <td>32.31</td>\n",
       "      <td>33.08</td>\n",
       "      <td>-0.023277</td>\n",
       "      <td>-770.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>002279</th>\n",
       "      <td>2018-03-16</td>\n",
       "      <td>2018-02-12</td>\n",
       "      <td>1000</td>\n",
       "      <td>12.42</td>\n",
       "      <td>10.72</td>\n",
       "      <td>0.158582</td>\n",
       "      <td>1700.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>002456</th>\n",
       "      <td>2018-03-16</td>\n",
       "      <td>2018-02-02</td>\n",
       "      <td>1000</td>\n",
       "      <td>21.31</td>\n",
       "      <td>19.15</td>\n",
       "      <td>0.112794</td>\n",
       "      <td>2160.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>300044</th>\n",
       "      <td>2018-03-16</td>\n",
       "      <td>2018-01-22</td>\n",
       "      <td>1000</td>\n",
       "      <td>9.64</td>\n",
       "      <td>8.70</td>\n",
       "      <td>0.108046</td>\n",
       "      <td>940.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>300287</th>\n",
       "      <td>2018-03-16</td>\n",
       "      <td>2018-01-19</td>\n",
       "      <td>1000</td>\n",
       "      <td>9.43</td>\n",
       "      <td>7.46</td>\n",
       "      <td>0.264075</td>\n",
       "      <td>1970.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>300431</th>\n",
       "      <td>2018-03-16</td>\n",
       "      <td>2018-02-08</td>\n",
       "      <td>1000</td>\n",
       "      <td>27.55</td>\n",
       "      <td>25.19</td>\n",
       "      <td>0.093688</td>\n",
       "      <td>2360.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>002837</th>\n",
       "      <td>2018-03-20</td>\n",
       "      <td>2018-02-07</td>\n",
       "      <td>1000</td>\n",
       "      <td>19.95</td>\n",
       "      <td>19.02</td>\n",
       "      <td>0.048896</td>\n",
       "      <td>930.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>300287</th>\n",
       "      <td>2018-03-21</td>\n",
       "      <td>2018-03-19</td>\n",
       "      <td>1000</td>\n",
       "      <td>9.57</td>\n",
       "      <td>9.89</td>\n",
       "      <td>-0.032356</td>\n",
       "      <td>-320.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>000100</th>\n",
       "      <td>2018-03-22</td>\n",
       "      <td>2018-02-22</td>\n",
       "      <td>1000</td>\n",
       "      <td>3.67</td>\n",
       "      <td>3.47</td>\n",
       "      <td>0.057637</td>\n",
       "      <td>200.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>000977</th>\n",
       "      <td>2018-03-23</td>\n",
       "      <td>2018-02-12</td>\n",
       "      <td>1000</td>\n",
       "      <td>20.49</td>\n",
       "      <td>16.33</td>\n",
       "      <td>0.254746</td>\n",
       "      <td>4160.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>603138</th>\n",
       "      <td>2018-03-23</td>\n",
       "      <td>2018-03-22</td>\n",
       "      <td>1000</td>\n",
       "      <td>40.12</td>\n",
       "      <td>43.07</td>\n",
       "      <td>-0.068493</td>\n",
       "      <td>-2950.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>002837</th>\n",
       "      <td>2018-04-04</td>\n",
       "      <td>2018-03-21</td>\n",
       "      <td>1000</td>\n",
       "      <td>22.04</td>\n",
       "      <td>21.96</td>\n",
       "      <td>0.003643</td>\n",
       "      <td>80.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>300738</th>\n",
       "      <td>2018-04-04</td>\n",
       "      <td>2018-03-26</td>\n",
       "      <td>1000</td>\n",
       "      <td>75.70</td>\n",
       "      <td>77.77</td>\n",
       "      <td>-0.026617</td>\n",
       "      <td>-2070.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>000977</th>\n",
       "      <td>2018-04-10</td>\n",
       "      <td>2018-03-26</td>\n",
       "      <td>1000</td>\n",
       "      <td>23.11</td>\n",
       "      <td>22.38</td>\n",
       "      <td>0.032618</td>\n",
       "      <td>730.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>002417</th>\n",
       "      <td>2018-04-10</td>\n",
       "      <td>2018-03-21</td>\n",
       "      <td>1000</td>\n",
       "      <td>11.54</td>\n",
       "      <td>11.55</td>\n",
       "      <td>-0.000866</td>\n",
       "      <td>-10.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>300738</th>\n",
       "      <td>2018-04-10</td>\n",
       "      <td>2018-04-09</td>\n",
       "      <td>1000</td>\n",
       "      <td>75.47</td>\n",
       "      <td>80.15</td>\n",
       "      <td>-0.058391</td>\n",
       "      <td>-4680.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>300365</th>\n",
       "      <td>2018-04-11</td>\n",
       "      <td>2018-03-26</td>\n",
       "      <td>1000</td>\n",
       "      <td>21.89</td>\n",
       "      <td>20.98</td>\n",
       "      <td>0.043375</td>\n",
       "      <td>910.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>300085</th>\n",
       "      <td>2018-04-13</td>\n",
       "      <td>2018-04-04</td>\n",
       "      <td>1000</td>\n",
       "      <td>16.34</td>\n",
       "      <td>16.80</td>\n",
       "      <td>-0.027381</td>\n",
       "      <td>-460.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>300383</th>\n",
       "      <td>2018-04-13</td>\n",
       "      <td>2018-03-20</td>\n",
       "      <td>1000</td>\n",
       "      <td>17.75</td>\n",
       "      <td>15.94</td>\n",
       "      <td>0.113551</td>\n",
       "      <td>1810.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>601928</th>\n",
       "      <td>2018-04-13</td>\n",
       "      <td>2018-04-11</td>\n",
       "      <td>1000</td>\n",
       "      <td>7.27</td>\n",
       "      <td>7.39</td>\n",
       "      <td>-0.016238</td>\n",
       "      <td>-120.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>300287</th>\n",
       "      <td>2018-04-17</td>\n",
       "      <td>2018-04-13</td>\n",
       "      <td>1000</td>\n",
       "      <td>9.56</td>\n",
       "      <td>9.80</td>\n",
       "      <td>-0.024490</td>\n",
       "      <td>-240.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>600589</th>\n",
       "      <td>2018-04-17</td>\n",
       "      <td>2018-04-13</td>\n",
       "      <td>1000</td>\n",
       "      <td>5.37</td>\n",
       "      <td>5.47</td>\n",
       "      <td>-0.018282</td>\n",
       "      <td>-100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>600770</th>\n",
       "      <td>2018-04-17</td>\n",
       "      <td>2018-04-11</td>\n",
       "      <td>1000</td>\n",
       "      <td>7.12</td>\n",
       "      <td>7.29</td>\n",
       "      <td>-0.023320</td>\n",
       "      <td>-170.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>300051</th>\n",
       "      <td>2018-04-20</td>\n",
       "      <td>2018-04-18</td>\n",
       "      <td>1000</td>\n",
       "      <td>11.29</td>\n",
       "      <td>12.00</td>\n",
       "      <td>-0.059167</td>\n",
       "      <td>-710.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>600590</th>\n",
       "      <td>2018-04-20</td>\n",
       "      <td>2018-04-13</td>\n",
       "      <td>1000</td>\n",
       "      <td>11.29</td>\n",
       "      <td>12.11</td>\n",
       "      <td>-0.067713</td>\n",
       "      <td>-820.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>600601</th>\n",
       "      <td>2018-04-23</td>\n",
       "      <td>2018-04-20</td>\n",
       "      <td>1000</td>\n",
       "      <td>3.08</td>\n",
       "      <td>3.09</td>\n",
       "      <td>-0.003236</td>\n",
       "      <td>-10.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>600845</th>\n",
       "      <td>2018-04-25</td>\n",
       "      <td>2018-04-11</td>\n",
       "      <td>1000</td>\n",
       "      <td>30.00</td>\n",
       "      <td>27.67</td>\n",
       "      <td>0.084207</td>\n",
       "      <td>2330.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>000066</th>\n",
       "      <td>2018-04-26</td>\n",
       "      <td>2018-03-27</td>\n",
       "      <td>1000</td>\n",
       "      <td>9.28</td>\n",
       "      <td>7.88</td>\n",
       "      <td>0.177665</td>\n",
       "      <td>1400.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>002063</th>\n",
       "      <td>2018-04-27</td>\n",
       "      <td>2018-04-26</td>\n",
       "      <td>1000</td>\n",
       "      <td>11.64</td>\n",
       "      <td>11.72</td>\n",
       "      <td>-0.006826</td>\n",
       "      <td>-80.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>601360</th>\n",
       "      <td>2018-04-27</td>\n",
       "      <td>2018-04-11</td>\n",
       "      <td>1000</td>\n",
       "      <td>37.80</td>\n",
       "      <td>41.58</td>\n",
       "      <td>-0.090909</td>\n",
       "      <td>-3780.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        sell_date   buy_date  amount  sell_price  buy_price  pnl_ratio  \\\n",
       "code                                                                     \n",
       "300367 2018-01-09 2018-01-02    1000       14.91      15.39  -0.031189   \n",
       "002456 2018-01-12 2018-01-02    1000       19.84      20.78  -0.045236   \n",
       "300036 2018-01-15 2018-01-03    1000       14.49      15.78  -0.081749   \n",
       "300245 2018-01-15 2018-01-10    1000       13.38      13.80  -0.030435   \n",
       "300290 2018-01-15 2018-01-02    1000        8.08       8.71  -0.072331   \n",
       "600198 2018-01-15 2018-01-03    1000       10.61      11.65  -0.089270   \n",
       "002544 2018-01-16 2018-01-02    1000       14.62      15.85  -0.077603   \n",
       "600718 2018-01-16 2018-01-03    1000       14.27      15.00  -0.048667   \n",
       "600804 2018-01-16 2018-01-03    1000       16.51      17.93  -0.079197   \n",
       "000063 2018-01-19 2018-01-16    1000       36.86      38.60  -0.045078   \n",
       "000100 2018-01-23 2018-01-03    1000        3.85       3.99  -0.035088   \n",
       "300052 2018-01-23 2018-01-12    1000       14.38      15.85  -0.092744   \n",
       "600797 2018-01-23 2018-01-02    1000       12.25      11.87   0.032013   \n",
       "600225 2018-01-29 2018-01-25    1000        4.91       5.02  -0.021912   \n",
       "000070 2018-01-31 2018-01-03    1000        9.45       9.52  -0.007353   \n",
       "002065 2018-01-31 2018-01-03    1000        7.99       8.53  -0.063306   \n",
       "002195 2018-01-31 2018-01-02    1000        6.16       5.91   0.042301   \n",
       "002335 2018-01-31 2018-01-03    1000       28.81      30.04  -0.040945   \n",
       "000066 2018-02-01 2018-01-24    1000        6.90       7.16  -0.036313   \n",
       "002279 2018-02-01 2018-01-19    1000       10.25      10.33  -0.007744   \n",
       "002396 2018-02-01 2018-01-31    1000       19.21      19.67  -0.023386   \n",
       "300297 2018-02-01 2018-01-17    1000        9.22       9.56  -0.035565   \n",
       "600105 2018-02-01 2018-01-02    1000        6.15       6.58  -0.065350   \n",
       "600804 2018-02-01 2018-01-19    1000       16.00      17.22  -0.070848   \n",
       "000836 2018-02-06 2018-01-24    1000        4.98       5.28  -0.056818   \n",
       "002095 2018-02-06 2018-01-22    1000       39.09      38.61   0.012432   \n",
       "601360 2018-03-02 2018-02-02    1000       52.51      55.03  -0.045793   \n",
       "300113 2018-03-07 2018-01-23    1000       22.67      18.38   0.233406   \n",
       "300113 2018-03-14 2018-03-12    1000       23.70      24.08  -0.015781   \n",
       "300212 2018-03-14 2018-03-09    1000       32.31      33.08  -0.023277   \n",
       "002279 2018-03-16 2018-02-12    1000       12.42      10.72   0.158582   \n",
       "002456 2018-03-16 2018-02-02    1000       21.31      19.15   0.112794   \n",
       "300044 2018-03-16 2018-01-22    1000        9.64       8.70   0.108046   \n",
       "300287 2018-03-16 2018-01-19    1000        9.43       7.46   0.264075   \n",
       "300431 2018-03-16 2018-02-08    1000       27.55      25.19   0.093688   \n",
       "002837 2018-03-20 2018-02-07    1000       19.95      19.02   0.048896   \n",
       "300287 2018-03-21 2018-03-19    1000        9.57       9.89  -0.032356   \n",
       "000100 2018-03-22 2018-02-22    1000        3.67       3.47   0.057637   \n",
       "000977 2018-03-23 2018-02-12    1000       20.49      16.33   0.254746   \n",
       "603138 2018-03-23 2018-03-22    1000       40.12      43.07  -0.068493   \n",
       "002837 2018-04-04 2018-03-21    1000       22.04      21.96   0.003643   \n",
       "300738 2018-04-04 2018-03-26    1000       75.70      77.77  -0.026617   \n",
       "000977 2018-04-10 2018-03-26    1000       23.11      22.38   0.032618   \n",
       "002417 2018-04-10 2018-03-21    1000       11.54      11.55  -0.000866   \n",
       "300738 2018-04-10 2018-04-09    1000       75.47      80.15  -0.058391   \n",
       "300365 2018-04-11 2018-03-26    1000       21.89      20.98   0.043375   \n",
       "300085 2018-04-13 2018-04-04    1000       16.34      16.80  -0.027381   \n",
       "300383 2018-04-13 2018-03-20    1000       17.75      15.94   0.113551   \n",
       "601928 2018-04-13 2018-04-11    1000        7.27       7.39  -0.016238   \n",
       "300287 2018-04-17 2018-04-13    1000        9.56       9.80  -0.024490   \n",
       "600589 2018-04-17 2018-04-13    1000        5.37       5.47  -0.018282   \n",
       "600770 2018-04-17 2018-04-11    1000        7.12       7.29  -0.023320   \n",
       "300051 2018-04-20 2018-04-18    1000       11.29      12.00  -0.059167   \n",
       "600590 2018-04-20 2018-04-13    1000       11.29      12.11  -0.067713   \n",
       "600601 2018-04-23 2018-04-20    1000        3.08       3.09  -0.003236   \n",
       "600845 2018-04-25 2018-04-11    1000       30.00      27.67   0.084207   \n",
       "000066 2018-04-26 2018-03-27    1000        9.28       7.88   0.177665   \n",
       "002063 2018-04-27 2018-04-26    1000       11.64      11.72  -0.006826   \n",
       "601360 2018-04-27 2018-04-11    1000       37.80      41.58  -0.090909   \n",
       "\n",
       "        pnl_money  \n",
       "code               \n",
       "300367     -480.0  \n",
       "002456     -940.0  \n",
       "300036    -1290.0  \n",
       "300245     -420.0  \n",
       "300290     -630.0  \n",
       "600198    -1040.0  \n",
       "002544    -1230.0  \n",
       "600718     -730.0  \n",
       "600804    -1420.0  \n",
       "000063    -1740.0  \n",
       "000100     -140.0  \n",
       "300052    -1470.0  \n",
       "600797      380.0  \n",
       "600225     -110.0  \n",
       "000070      -70.0  \n",
       "002065     -540.0  \n",
       "002195      250.0  \n",
       "002335    -1230.0  \n",
       "000066     -260.0  \n",
       "002279      -80.0  \n",
       "002396     -460.0  \n",
       "300297     -340.0  \n",
       "600105     -430.0  \n",
       "600804    -1220.0  \n",
       "000836     -300.0  \n",
       "002095      480.0  \n",
       "601360    -2520.0  \n",
       "300113     4290.0  \n",
       "300113     -380.0  \n",
       "300212     -770.0  \n",
       "002279     1700.0  \n",
       "002456     2160.0  \n",
       "300044      940.0  \n",
       "300287     1970.0  \n",
       "300431     2360.0  \n",
       "002837      930.0  \n",
       "300287     -320.0  \n",
       "000100      200.0  \n",
       "000977     4160.0  \n",
       "603138    -2950.0  \n",
       "002837       80.0  \n",
       "300738    -2070.0  \n",
       "000977      730.0  \n",
       "002417      -10.0  \n",
       "300738    -4680.0  \n",
       "300365      910.0  \n",
       "300085     -460.0  \n",
       "300383     1810.0  \n",
       "601928     -120.0  \n",
       "300287     -240.0  \n",
       "600589     -100.0  \n",
       "600770     -170.0  \n",
       "300051     -710.0  \n",
       "600590     -820.0  \n",
       "600601      -10.0  \n",
       "600845     2330.0  \n",
       "000066     1400.0  \n",
       "002063      -80.0  \n",
       "601360    -3780.0  "
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Performance.pnl_fifo"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<module 'matplotlib.pyplot' from 'C:\\\\ProgramData\\\\Anaconda3\\\\lib\\\\site-packages\\\\matplotlib\\\\pyplot.py'>"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "Performance.plot_pnlmoney(Performance.pnl_fifo)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## STEP6: 存储结果"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "Account.save()\n",
    "Risk.save()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## STEP7: 查看存储的结果"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "account_info=QA.QA_fetch_account({'account_cookie':'JCSC_EXAMPLE'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "account=QA.QA_Account().from_message(account_info[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "< QA_Account JCSC_EXAMPLE>"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "account"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
